Triple
T16667651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Equal Rights Association |
E405022
|
entity |
| Predicate | organized event |
P35067
|
FINISHED |
| Object | 1866 American Equal Rights Association convention |
—
|
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: 1866 American Equal Rights Association convention | Statement: [American Equal Rights Association, organized event, 1866 American Equal Rights Association convention]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: organized event Context triple: [American Equal Rights Association, organized event, 1866 American Equal Rights Association convention]
-
A.
organisedEvent
chosen
Indicates that an entity planned, coordinated, and carried out an event.
-
B.
eventTypeOrganized
Indicates that an entity organized or arranged a specific type or category of event.
-
C.
organizedAt
Indicates that an event or activity was arranged, planned, or hosted at a specific location or venue.
-
D.
oftenOrganizedBy
Indicates that an event, activity, or process is frequently arranged, coordinated, or hosted by a particular agent or entity.
-
E.
organisedFor
Indicates that something has been arranged, structured, or coordinated specifically to serve, support, or benefit a particular entity or purpose.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c9d9fc48190a8156c029668b544 |
completed | April 18, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.