Triple
T5442439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1st Academy Awards |
E122166
|
entity |
| Predicate | numberOfGuests |
P2307
|
FINISHED |
| Object | 270 |
—
|
LITERAL 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: 270 | Statement: [1st Academy Awards, numberOfGuests, 270]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGuests Context triple: [1st Academy Awards, numberOfGuests, 270]
-
A.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
-
B.
numberOfPersons
chosen
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
C.
relationshipWithGuests
Indicates the nature or status of the connection or interaction that someone has with their guests.
-
D.
seatsForParty
Indicates that a seating arrangement or capacity is designated to accommodate a specific party or group.
-
E.
maximumNumberOfKnightsAndLadies
Indicates the greatest allowable or observed count of entities classified as knights and ladies within a given context or scenario.
- F. None of above.
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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.