Triple
T27288153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadine Lustre |
E688537
|
entity |
| Predicate | isMultimediaStarIn |
P162535
|
FINISHED |
| Object | Philippine entertainment industry |
—
|
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: Philippine entertainment industry | Statement: [Nadine Lustre, isMultimediaStarIn, Philippine entertainment industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMultimediaStarIn Context triple: [Nadine Lustre, isMultimediaStarIn, Philippine entertainment industry]
-
A.
isPrimaryStarOf
Indicates that a star serves as the main or central stellar object in relation to a specified system, object, or context.
-
B.
isNamedStarOf
Indicates that an entity is the officially designated or commonly recognized star of another entity (such as a show, film, or event).
-
C.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
D.
starIsAlsoSinger
Indicates that the person who is a star also has the role or occupation of a singer.
-
E.
laterDepictedIn
Indicates that an entity is portrayed or represented in a depiction (such as an image, artwork, or illustration) that was created at a later time than the entity itself.
- 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_69ef355998e08190bdff849e8f33adce |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f625402d808190be8279d895d2b27f |
completed | May 2, 2026, 4:24 p.m. |
Created at: April 27, 2026, 11:13 a.m.