Triple
T26957439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant family |
E678944
|
entity |
| Predicate | memberInvolvedIn |
P34269
|
FINISHED |
| Object | Mexican–American War |
—
|
NE NERFINISHED |
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: Mexican–American War | Statement: [Grant family, memberInvolvedIn, Mexican–American War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberInvolvedIn Context triple: [Grant family, memberInvolvedIn, Mexican–American War]
-
A.
hasMemberInvolvedIn
chosen
Indicates that a group or collective entity has at least one of its members participating in or engaged with a specified activity, event, or situation.
-
B.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
C.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
-
D.
relativeInvolvedInEvent
Indicates that a person’s relative participates in, is affected by, or is otherwise involved in a particular event.
-
E.
closelyInvolvedWith
Indicates a relationship in which one entity is deeply and actively engaged with another’s activities, decisions, or affairs.
- 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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 27, 2026, 6:28 a.m.