Triple
T15972007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carrie Ann Inaba |
E387347
|
entity |
| Predicate | hasHealthCondition |
P1005
|
FINISHED |
| Object |
Sjögren syndrome
Sjögren syndrome is a chronic autoimmune disease in which the immune system attacks the body’s moisture-producing glands, commonly causing dry eyes and dry mouth along with fatigue and joint pain.
|
E1186370
|
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: Sjögren syndrome | Statement: [Carrie Ann Inaba, hasHealthCondition, Sjögren syndrome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sjögren syndrome Context triple: [Carrie Ann Inaba, hasHealthCondition, Sjögren syndrome]
-
A.
SLE
SLE is a mid-level trim package for GMC vehicles that typically adds upgraded comfort, convenience, and appearance features over the base model.
-
B.
SLE
SLE is the IATA airport code for Salem Municipal Airport, a public airport serving Salem, Oregon, in the United States.
-
C.
SLE
SLE (Software Language Engineering) is a conference focused on the theory, design, implementation, and application of software languages and language-based tools.
-
D.
SLE
SLE is the three-letter ISO 3166-1 alpha-3 country code assigned to Sierra Leone.
-
E.
SLE
SLE is a commuter rail service operating along the Connecticut shoreline, connecting towns between New London and New Haven.
- 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: Sjögren syndrome Triple: [Carrie Ann Inaba, hasHealthCondition, Sjögren syndrome]
Generated description
Sjögren syndrome is a chronic autoimmune disease in which the immune system attacks the body’s moisture-producing glands, commonly causing dry eyes and dry mouth along with fatigue and joint pain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sjögren syndrome Target entity description: Sjögren syndrome is a chronic autoimmune disease in which the immune system attacks the body’s moisture-producing glands, commonly causing dry eyes and dry mouth along with fatigue and joint pain.
-
A.
SLE
SLE is a mid-level trim package for GMC vehicles that typically adds upgraded comfort, convenience, and appearance features over the base model.
-
B.
SLE
SLE is the IATA airport code for Salem Municipal Airport, a public airport serving Salem, Oregon, in the United States.
-
C.
SLE
SLE (Software Language Engineering) is a conference focused on the theory, design, implementation, and application of software languages and language-based tools.
-
D.
SLE
SLE is the three-letter ISO 3166-1 alpha-3 country code assigned to Sierra Leone.
-
E.
SLE
SLE is a commuter rail service operating along the Connecticut shoreline, connecting towns between New London and New Haven.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15729d73c8190a4140a0e55ee2566 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe8afa288190838cb35b8a4fcf50 |
completed | May 9, 2026, 11:08 p.m. |
| NEDg | Description generation | batch_69ffbf3f40288190a59646124e06a864 |
completed | May 9, 2026, 11:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffbfddd0348190baab794f613c71bf |
completed | May 9, 2026, 11:14 p.m. |
Created at: April 10, 2026, 4:54 a.m.