Triple
T23378619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Labouchere Amendment |
E593675
|
entity |
| Predicate | wordingCharacterization |
P662
|
FINISHED |
| Object | broadly worded |
—
|
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: broadly worded | Statement: [Labouchere Amendment, wordingCharacterization, broadly worded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wordingCharacterization Context triple: [Labouchere Amendment, wordingCharacterization, broadly worded]
-
A.
textualCharacterization
Indicates that one entity provides a descriptive or narrative characterization of another entity, typically in textual form.
-
B.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
C.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
D.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
responseCharacterization
Indicates how a given response is evaluated or described in terms of its qualities, attributes, or type.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b5e4f0819081a5d4586796677b |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:33 p.m.