Triple
T1590404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandy Lerner |
E34165
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sandy |
E37229
|
NE FINISHED |
How this triple was built (2 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: Sandy | Statement: [Sandy Lerner, givenName, Sandy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sandy Context triple: [Sandy Lerner, givenName, Sandy]
-
A.
Sandy
chosen
Sandy is a common nickname or short form of the given name Alexander.
-
B.
Sandy
Sandy is a fictional character from Mark Twain’s satirical novel "A Connecticut Yankee in King Arthur’s Court," known as a medieval woman who becomes the companion and later wife of the time-traveling protagonist.
-
C.
Hayden
Hayden is a surname most notably associated with American actor and author Sterling Hayden, known for his roles in classic mid-20th-century films.
-
D.
Dreezy
Dreezy is an American rapper and singer from Chicago known for her sharp lyricism and contributions to the city's contemporary hip-hop scene.
-
E.
Mari
Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa621526e8819097d8c5330e527ed3 |
completed | March 6, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad46a0f5348190ae3fe8033360d800 |
completed | March 8, 2026, 9:51 a.m. |
Created at: March 4, 2026, 7:27 p.m.