Triple
T38048774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Alexandre Manette |
E949694
|
entity |
| Predicate | testifiesAt |
P4080
|
FINISHED |
| Object | Charles Darnay’s trial in Paris |
—
|
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: Charles Darnay’s trial in Paris | Statement: [Dr. Alexandre Manette, testifiesAt, Charles Darnay’s trial in Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testifiesAt Context triple: [Dr. Alexandre Manette, testifiesAt, Charles Darnay’s trial in Paris]
-
A.
gaveTestimonyIn
chosen
Indicates that one entity provided formal testimony or a statement in an official proceeding, event, or context associated with another entity.
-
B.
mayTestifyBefore
Indicates that one entity is permitted or authorized to give testimony or evidence in front of another entity or formal body.
-
C.
hasTestimony
Indicates that an entity provides, contains, or is associated with a formal statement or account (testimony) about another entity or event.
-
D.
testimonyAffects
Indicates that one party’s testimony has an influence or impact on another entity, situation, or outcome.
-
E.
soughtTestimonyAgainst
Indicates that one party actively attempted to obtain another party’s testimony to be used against a specified target in a legal or investigative context.
- 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_69f76f000cf081908c11fb5443b392e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc44c7e73c819082d4fc1900fb9632 |
completed | May 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69fbc8efffbc8190a139798ad1880526 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.