Triple
T17118729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nini |
E415406
|
entity |
| Predicate | relationshipToLocation |
P112751
|
FINISHED |
| Object | performs at the Moulin Rouge nightclub |
—
|
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: performs at the Moulin Rouge nightclub | Statement: [Nini, relationshipToLocation, performs at the Moulin Rouge nightclub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToLocation Context triple: [Nini, relationshipToLocation, performs at the Moulin Rouge nightclub]
-
A.
personAssociatedPlace
chosen
Indicates that a person has a notable connection or association with a particular place, such as residence, origin, work, or frequent presence.
-
B.
relatedPlace
Indicates a relationship where one place is connected or associated with another place in a relevant or meaningful way.
-
C.
residesNear
Indicates that one entity lives or is located in close physical proximity to another entity.
-
D.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
E.
relationshipToState
Indicates a relationship or connection that an entity has with a particular state or governmental body.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e8086a388190a655a044feccab14 |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.