Triple
T22454487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harley Quinn Smith |
E555079
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Harley |
—
|
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: Harley | Statement: [Harley Quinn Smith, givenName, Harley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harley Context triple: [Harley Quinn Smith, givenName, Harley]
-
A.
Harley
Harley is the central protagonist of Tyler Perry’s film "Temptation: Confessions of a Marriage Counselor," whose personal and marital struggles drive the story’s exploration of infidelity and its consequences.
-
B.
Harley
Harley is an English surname historically associated with prominent political figures such as Robert Harley, 1st Earl of Oxford and Earl Mortimer.
-
C.
Harley
Harley is the given name of the English actor, director, and playwright Granville Barker, a key figure in early 20th-century British theatre.
-
D.
Harley
chosen
Harley is a given name commonly used for both males and females, often associated with English-speaking countries.
-
E.
Harley
Harley is a small settlement in Shropshire, England, situated near the A458 road.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4e2bd4819083e5bed44e9776c6 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 16, 2026, 8:48 p.m.