Triple
T27650900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actress – Broadcast News |
E696850
|
entity |
| Predicate | lostToPerformance |
P356
|
FINISHED |
| Object | Cher in Moonstruck |
—
|
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: Cher in Moonstruck | Statement: [Academy Award for Best Actress – Broadcast News, lostToPerformance, Cher in Moonstruck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lostToPerformance Context triple: [Academy Award for Best Actress – Broadcast News, lostToPerformance, Cher in Moonstruck]
-
A.
lostDuring
Indicates that something ceased to be in possession or was no longer retained while a particular event, process, or time period was occurring.
-
B.
lostTo
chosen
Indicates that one entity was defeated by another in a competition, conflict, or comparison.
-
C.
lost
Indicates that an entity no longer possesses or has been deprived of another entity it previously had.
-
D.
lostWith
Indicates that one entity experienced a loss or defeat in conjunction with, or as part of the same side/team as, another entity.
-
E.
lostPowerIn
Indicates that an entity has experienced a loss of electrical or functional power while in or at a specified location or context.
- 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_69ef590abd3c8190834d0193bde12007 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f631d4dfbc819094c0e200e214ec08 |
completed | May 2, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:31 p.m.