Triple
T972076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir |
E20965
|
entity |
| Predicate | typicalPrecedence |
P1803
|
FINISHED |
| Object | precedes personal name in written style |
—
|
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: precedes personal name in written style | Statement: [Sir, typicalPrecedence, precedes personal name in written style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPrecedence Context triple: [Sir, typicalPrecedence, precedes personal name in written style]
-
A.
orderPrecedence
chosen
Indicates that one entity must come before another in a defined sequence or priority order.
-
B.
confersPrecedenceIn
Indicates that one entity is granted higher priority, rank, or standing over another within a specified context or domain.
-
C.
precedentFor
Indicates that one situation, decision, or case serves as an authoritative example or basis for deciding or interpreting another.
-
D.
hasLowerPrecedenceThan
Indicates that one item is ranked or ordered with a lower priority or importance compared to another item.
-
E.
precedentSystem
Indicates that one legal system or framework serves as a source of precedent or authoritative guidance for another system.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b44c38f08190997e141d424e9e04 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.