Triple
T20248697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eli |
E498491
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Haley |
—
|
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: Haley | Statement: [Eli, character, Haley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haley Context triple: [Eli, character, Haley]
-
A.
Haley
chosen
Haley is a surname most notably associated with American actor Jack Haley, who played the Tin Man in the classic film "The Wizard of Oz."
-
B.
Hailey
Hailey is a parish in Hertfordshire, England, associated with the town of Haileybury.
-
C.
Hailey
Hailey is a small rural village located within the district of West Oxfordshire in England.
-
D.
Hailey
Hailey is an American model and media personality best known for her high-profile fashion work and marriage to musician Justin Bieber.
-
E.
Hailey
Hailey is a small city in south-central Idaho known as a gateway to the Sun Valley resort area and the surrounding Sawtooth National Forest.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a5ce4081908dff86ed4c613fd6 |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.