Triple
T11947324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodyguard |
E284333
|
entity |
| Predicate | hasOpeningScene |
P102412
|
FINISHED |
| Object | train suicide bombing attempt |
—
|
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: train suicide bombing attempt | Statement: [Bodyguard, hasOpeningScene, train suicide bombing attempt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningScene Context triple: [Bodyguard, hasOpeningScene, train suicide bombing attempt]
-
A.
hasOpeningFeature
Indicates that an entity possesses a specific characteristic, element, or attribute related to its opening or entry point.
-
B.
openingSceneTime
Indicates the specific time at which the opening scene of a work (e.g., film, play, or episode) takes place within its narrative.
-
C.
hasOpeningCreditsUsage
Indicates that something is used or appears specifically in the opening credits of a work.
-
D.
hasOpeningMovement
Indicates that a work, performance, or sequence includes a distinct initial movement or section that begins the overall piece.
-
E.
hasOpening
Indicates that one entity possesses or features an opening, gap, or entrance that allows access, passage, or exposure.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903456ec0819082b8b10755a6b732 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:45 p.m.