Triple
T33853375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally |
E867695
|
entity |
| Predicate | meetsDuringEvent |
P3123
|
FINISHED |
| Object | car accident |
—
|
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: car accident | Statement: [Sally, meetsDuringEvent, car accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsDuringEvent Context triple: [Sally, meetsDuringEvent, car accident]
-
A.
meetsDuring
chosen
Indicates that one entity encounters or comes together with another while a specified event or time interval is in progress.
-
B.
meetsForEvent
Indicates that two or more entities come together at the same place and time specifically to participate in a particular event.
-
C.
meetsWhen
Indicates that two entities come together or encounter each other at a specific time or under particular temporal conditions.
-
D.
meetsBy
Indicates that one entity encounters or comes together with another entity, typically at a specific time or place.
-
E.
eventInConflict
Indicates that an event occurs within, is part of, or is directly associated with a specific conflict.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:47 a.m.