Triple
T32776400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire Keesey |
E838218
|
entity |
| Predicate | firstMeetsDuring |
P3123
|
FINISHED |
| Object | bank robbery at Cambridge Merchants Bank |
—
|
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: bank robbery at Cambridge Merchants Bank | Statement: [Claire Keesey, firstMeetsDuring, bank robbery at Cambridge Merchants Bank]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMeetsDuring Context triple: [Claire Keesey, firstMeetsDuring, bank robbery at Cambridge Merchants Bank]
-
A.
meetsDuring
chosen
Indicates that one entity encounters or comes together with another while a specified event or time interval is in progress.
-
B.
meetsBefore
Indicates that one entity encounters or meets another at some point in time that occurs earlier than a specified reference meeting or event.
-
C.
firstMeets
Indicates that one entity encounters or comes into contact with another entity for the first time.
-
D.
meetsWhen
Indicates that two entities come together or encounter each other at a specific time or under particular temporal conditions.
-
E.
meetsInTimePeriod
Indicates that two entities encounter or come together during a specified time period.
- 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_69f3493a824c8190938489ba69041d08 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:13 a.m.