Triple
T25317901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Titanic (Broadway musical) |
E634796
|
entity |
| Predicate | portraysHistoricalFigures |
P53504
|
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: [Titanic (Broadway musical), portraysHistoricalFigures, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysHistoricalFigures Context triple: [Titanic (Broadway musical), portraysHistoricalFigures, true]
-
A.
basedOnHistoricalFigure
Indicates that something is derived from, inspired by, or modeled after a real historical person.
-
B.
usesRealHistoricalFigures
chosen
Indicates that the work includes or depicts actual people from real history rather than entirely fictional characters.
-
C.
historicalFigure
Indicates that an entity is recognized as a notable person from the past who played a significant role in history.
-
D.
historicalFigureTypeCovered
Indicates that a given type or category of historical figure is included or addressed within a particular context, work, or dataset.
-
E.
portraysHumanHistoryAs
Indicates that one entity represents or depicts human history in a particular way or from a specific perspective.
- 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_69e75a9847c08190bb02990d06d5ffb7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 21, 2026, 1:28 p.m.