Triple
T12160909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of La Angostura |
E289702
|
entity |
| Predicate | MexicanCasualtiesAndLosses |
P34188
|
FINISHED |
| Object | over 600 killed |
—
|
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: over 600 killed | Statement: [Battle of La Angostura, MexicanCasualtiesAndLosses, over 600 killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MexicanCasualtiesAndLosses Context triple: [Battle of La Angostura, MexicanCasualtiesAndLosses, over 600 killed]
-
A.
casualtiesMexicanKilled
chosen
Indicates that the event or action resulted in Mexican individuals being killed as casualties.
-
B.
battleCommanderMexican
Indicates that one entity serves as the Mexican commander or leading military officer in a particular battle involving the other entity.
-
C.
militaryCommanderMexican
Indicates that one entity serves as the military commander of the other entity, specifically within a Mexican military context.
-
D.
MexicanObjective
Indicates that an entity has an objective, goal, or target specifically related to Mexico or Mexican affairs.
-
E.
strengthMexico
Indicates a relationship where some form of strength, power, or robustness is attributed to, associated with, or exerted by Mexico.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.