Triple
T828120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Statutes of the Realm |
E17900
|
entity |
| Predicate | containsTextOf |
P7166
|
FINISHED |
| Object | public general acts |
—
|
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: public general acts | Statement: [The Statutes of the Realm, containsTextOf, public general acts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsTextOf Context triple: [The Statutes of the Realm, containsTextOf, public general acts]
-
A.
containsText
Indicates that one entity includes the specified text string within its content.
-
B.
hasText
chosen
Indicates that an entity is associated with or contains a specific piece of textual content.
-
C.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
D.
containsMostOf
Indicates that one entity includes the majority (but not necessarily all) of the substance, elements, or components of another entity.
-
E.
containsPass
Indicates that one entity includes or holds a valid pass or authorization credential within it.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab99b1e48190afad1f073348b29a |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.