Triple
T34984374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bridge |
E1008900
|
entity |
| Predicate | hasDetectivePlot |
P175876
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Bridge, hasDetectivePlot, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDetectivePlot Context triple: [The Bridge, hasDetectivePlot, true]
-
A.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
B.
hasMultipleSuspectsInPlot
Indicates that a plot or scheme involves more than one individual as suspects.
-
C.
hasClericalDetective
Indicates that an entity includes or is associated with a detective who is also a member of the clergy.
-
D.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
E.
hasSleuth
chosen
Indicates that an entity is associated with or employs a sleuth (detective) responsible for investigating on its behalf.
- 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_69f76dc844a48190881951fffb83d17e |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff32b88bf48190b45afd1b60cb511c |
completed | May 9, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69ff3031e18881908927b2ab452de863 |
completed | May 9, 2026, 1:01 p.m. |
Created at: May 3, 2026, 4:01 p.m.