Triple
T30990821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmelita |
E789660
|
entity |
| Predicate | protagonistLocation |
P177165
|
FINISHED |
| Object | Los Angeles |
—
|
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: Los Angeles | Statement: [Carmelita, protagonistLocation, Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistLocation Context triple: [Carmelita, protagonistLocation, Los Angeles]
-
A.
antagonistLocationFor
Indicates that a location serves as the primary place where an antagonist operates, resides, or exerts influence in relation to a given context or entity.
-
B.
climaxLocation
Indicates the place or setting where the most intense or pivotal moment of an event, narrative, or process occurs.
-
C.
placeOfSetting
Indicates the location or environment where an event, scene, or situation takes place.
-
D.
homeLocationInStory
Indicates the place that serves as a character’s primary home or base of residence within the context of the story.
-
E.
notableGameLocation
Indicates that a particular place is recognized as a significant or prominent location within a game.
- 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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f854486c81909396d944a55e03ab |
completed | May 3, 2026, 7:25 a.m. |
Created at: April 29, 2026, 8:56 p.m.