Triple
T10244414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halle Bailey |
E240175
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bailey |
E399816
|
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: Bailey | Statement: [Halle Bailey, familyName, Bailey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bailey Context triple: [Halle Bailey, familyName, Bailey]
-
A.
Bailey
Bailey is a beluga whale character in Pixar's animated film "Finding Dory," known for his humorous struggles and eventual skill with echolocation.
-
B.
Bailey
Bailey is the original surname of famed American abolitionist and orator Frederick Douglass.
-
C.
Bailey
Bailey is the given first name of the renowned cryptographer Whitfield Diffie, a pioneer of public-key cryptography.
-
D.
Bailey
Bailey is a central character in Flannery O’Connor’s short story “A Good Man Is Hard to Find,” serving as the weary, practical father whose family road trip spirals into tragedy.
-
E.
Bailey
chosen
Bailey is a common English surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d22a76188190a73df23bfb08eb3d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7936ce4819087f07df2c7a76282 |
completed | April 9, 2026, 12:49 a.m. |
Created at: April 6, 2026, 11:26 a.m.