Triple
T32484718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture for "Chariots of Fire" |
E830205
|
entity |
| Predicate | competedInCategoryWith |
P183745
|
FINISHED |
| Object | Atlantic City |
—
|
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: Atlantic City | Statement: [Academy Award for Best Picture for "Chariots of Fire", competedInCategoryWith, Atlantic City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competedInCategoryWith Context triple: [Academy Award for Best Picture for "Chariots of Fire", competedInCategoryWith, Atlantic City]
-
A.
competedAs
Indicates that an entity participated in a competition or contest in the role, category, or capacity specified by another entity.
-
B.
hasCompetitionCategory
Indicates that an entity is associated with a specific category or division within a competition.
-
C.
competedFor
Indicates that an entity took part in a contest, rivalry, or competition in pursuit of another entity (such as a prize, position, or resource).
-
D.
competedInDiscipline
Indicates that an entity took part in a competition or event within a specific discipline or category.
-
E.
competitorCategory
Indicates that two entities operate in the same competitive category or market segment, positioning them as rivals within that domain.
- F. None of above. chosen
Provenance (4 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7a283388c81908e4a9ee3369e8d6f |
completed | May 3, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a224365081908ff6958e3b30bd05 |
completed | May 3, 2026, 7:29 p.m. |
Created at: May 1, 2026, 12:58 a.m.