Triple
T26651880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women of All Nations |
E669081
|
entity |
| Predicate | featuresComedyTeam |
P131747
|
FINISHED |
| Object | Laurel and Hardy |
—
|
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: Laurel and Hardy | Statement: [Women of All Nations, featuresComedyTeam, Laurel and Hardy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresComedyTeam Context triple: [Women of All Nations, featuresComedyTeam, Laurel and Hardy]
-
A.
associatedWithComedyTeam
Indicates a relationship where an entity is or has been part of, working with, or otherwise linked to a specific comedy team.
-
B.
featuredTeam
Indicates that a particular team is highlighted or given special prominence in a given context or presentation.
-
C.
featuresTroupe
Indicates that something includes or presents a particular troupe as part of its content or composition.
-
D.
featuresTeams
chosen
Indicates that something prominently presents or includes specific teams as a central element or focus.
-
E.
featureCrew
Indicates that a particular crew member is highlighted or designated as a featured participant within a crew-related 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 27, 2026, 2:33 a.m.