Triple
T1208365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia Nasar |
E25941
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nasar |
E25941
|
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: Nasar | Statement: [Sylvia Nasar, familyName, Nasar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nasar Context triple: [Sylvia Nasar, familyName, Nasar]
-
A.
Nasar
chosen
Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
-
B.
Hazaragi
Hazaragi is a variety of Persian primarily spoken by the Hazara people of central Afghanistan and surrounding regions, distinguished by its unique phonology and significant Turkic and Mongolic influences.
-
C.
Ndowe
Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
-
D.
Masri
Masri is a widely spoken modern Arabic dialect used primarily in Egypt, especially in everyday conversation and popular media.
-
E.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8f6ff3048190a420ee6c92fc9c71 |
completed | March 7, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:46 p.m.