Triple
T37367786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolf Hall (stage play) |
E927757
|
entity |
| Predicate | characterInclusion |
P12208
|
FINISHED |
| Object | members of the Tudor court |
—
|
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: members of the Tudor court | Statement: [Wolf Hall (stage play), characterInclusion, members of the Tudor court]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInclusion Context triple: [Wolf Hall (stage play), characterInclusion, members of the Tudor court]
-
A.
characterCorrespondsTo
Indicates that one character is equivalent to, maps onto, or represents another character in a defined correspondence or mapping.
-
B.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
C.
containsCharacterAction
Indicates that an entity includes or features an action performed by a character within it.
-
D.
characterIn
chosen
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
characterCoverage
Indicates that one entity provides or includes sufficient representation or support for the characters (e.g., glyphs, symbols, or scripts) required or used by another 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffebbd9bac8190b3dca4b7252a2278 |
completed | May 10, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_69ffe93120a08190a44bb64d052eda78 |
completed | May 10, 2026, 2:10 a.m. |
Created at: May 3, 2026, 4:16 p.m.