Triple
T22791886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidney Drell |
E564132
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sidney |
—
|
NE NERFINISHED |
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: Sidney | Statement: [Sidney Drell, givenName, Sidney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sidney Context triple: [Sidney Drell, givenName, Sidney]
-
A.
Sidney
Sidney is the given name of Sid Luft, the American show business figure best known as the third husband and manager of entertainer Judy Garland.
-
B.
Sidney
Sidney is the given first name of the American rapper known professionally as Desiigner.
-
C.
Sidney
Sidney is a small coastal town on Vancouver Island in British Columbia, Canada, known for its waterfront, ferry connections, and proximity to Victoria.
-
D.
Sidney
chosen
Sidney is a given name shared by various notable individuals across fields such as literature, politics, and entertainment.
-
E.
Sidney
Sidney is an English surname historically associated with the prominent Sidney family, including figures such as Frances Sidney, Countess of Sussex.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cd5778c81909a18317ff98e341c |
completed | April 29, 2026, 3:36 a.m. |
Created at: April 17, 2026, 3:30 p.m.