Triple
T18991001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | assassination of Pancho Villa |
E464680
|
entity |
| Predicate | victimPoliticalStatus |
P134057
|
FINISHED |
| Object | retired revolutionary caudillo |
—
|
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: retired revolutionary caudillo | Statement: [assassination of Pancho Villa, victimPoliticalStatus, retired revolutionary caudillo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimPoliticalStatus Context triple: [assassination of Pancho Villa, victimPoliticalStatus, retired revolutionary caudillo]
-
A.
victimStatus
Indicates the condition or state of a person who has been harmed or wronged as a result of an event, action, or offense.
-
B.
victimParty
Indicates that one party is the victim or harmed side in an event, action, or situation involving another party.
-
C.
victimState
Indicates the condition or status that a victim is in as a result of an event, action, or harmful incident.
-
D.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
E.
victimSide
Indicates that one entity is on, represents, or corresponds to the side of the victim in a conflict, incident, or harmful event.
- F. None of above. chosen
Provenance (4 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d67dee4c8190ac2017ff748ea6aa |
completed | April 20, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f88e0c81908cb20f08bf24cd32 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:01 p.m.