Triple
T36136684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Gordon Jr. (The Dark Knight film) |
E1045186
|
entity |
| Predicate | importantSceneLocation |
P3858
|
FINISHED |
| Object | Gotham City construction site |
—
|
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: Gotham City construction site | Statement: [James Gordon Jr. (The Dark Knight film), importantSceneLocation, Gotham City construction site]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: importantSceneLocation Context triple: [James Gordon Jr. (The Dark Knight film), importantSceneLocation, Gotham City construction site]
-
A.
notableGameLocation
Indicates that a particular place is recognized as a significant or prominent location within a game.
-
B.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
C.
climaxLocation
Indicates the place or setting where the most intense or pivotal moment of an event, narrative, or process occurs.
-
D.
notableLocation
chosen
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
E.
significantEventPlace
Indicates the place where a significant event occurred or is associated with an entity.
- 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_69f76e36a4508190b5bfc8f594272a4c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.