Triple
T4160765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kocher sign |
E91527
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object |
Graves disease
Graves disease is an autoimmune disorder that causes hyperthyroidism, leading to symptoms such as weight loss, heat intolerance, goiter, and characteristic eye manifestations.
|
E417002
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Graves disease | Statement: [Kocher sign, associatedWith, Graves disease]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Graves disease Context triple: [Kocher sign, associatedWith, Graves disease]
-
A.
Graves
Graves is a renowned wine-producing subregion on the left bank of Bordeaux, France, famous for its gravelly soils and high-quality red and white wines.
-
B.
Hashimoto
Hashimoto is a city in Wakayama Prefecture, Japan, known as a regional hub between Osaka and the Kii Mountain range.
-
C.
Graves classification
Graves classification is a Bordeaux wine classification system that ranks and recognizes the quality of wines produced in the Graves region of Bordeaux, France.
-
D.
Struma
The Struma is a significant river in the Balkans that flows from western Bulgaria into Greece, ultimately emptying into the Aegean Sea.
-
E.
SLE
SLE is the three-letter ISO 3166-1 alpha-3 country code assigned to Sierra Leone.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Graves disease Triple: [Kocher sign, associatedWith, Graves disease]
Generated description
Graves disease is an autoimmune disorder that causes hyperthyroidism, leading to symptoms such as weight loss, heat intolerance, goiter, and characteristic eye manifestations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Graves disease Target entity description: Graves disease is an autoimmune disorder that causes hyperthyroidism, leading to symptoms such as weight loss, heat intolerance, goiter, and characteristic eye manifestations.
-
A.
Graves
Graves is a renowned wine-producing subregion on the left bank of Bordeaux, France, famous for its gravelly soils and high-quality red and white wines.
-
B.
Hashimoto
Hashimoto is a city in Wakayama Prefecture, Japan, known as a regional hub between Osaka and the Kii Mountain range.
-
C.
Graves classification
Graves classification is a Bordeaux wine classification system that ranks and recognizes the quality of wines produced in the Graves region of Bordeaux, France.
-
D.
Struma
The Struma is a significant river in the Balkans that flows from western Bulgaria into Greece, ultimately emptying into the Aegean Sea.
-
E.
SLE
SLE is a mid-level trim package for GMC vehicles that typically adds upgraded comfort, convenience, and appearance features over the base model.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af029454d08190b7ff32776081fabc |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f42f2cc8190ae10ea12273c930a |
completed | March 14, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_69b5800a12e48190b184373464930b1e |
completed | March 14, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b580af3eb88190a89d5827e32293c1 |
completed | March 14, 2026, 3:37 p.m. |
Created at: March 9, 2026, 3:44 p.m.