Triple
T942929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Noche Triste |
E20345
|
entity |
| Predicate | approximateSpanishCasualties |
P661
|
FINISHED |
| Object | hundreds 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: hundreds killed | Statement: [La Noche Triste, approximateSpanishCasualties, hundreds killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateSpanishCasualties Context triple: [La Noche Triste, approximateSpanishCasualties, hundreds killed]
-
A.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
B.
roleInSpanishCivilWar
Indicates the specific involvement or function an entity had in the context of the Spanish Civil War.
-
C.
casualtiesEstimate
chosen
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
D.
commanderForSpain
Indicates that a person serves or has served as a military commander on behalf of Spain.
-
E.
hasSignificantSpanishInfluence
Indicates that one entity has been strongly shaped or notably affected by Spanish culture, language, practices, or presence.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a2b1ec8190a2753ad3b3e8cc7a |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29dc8dc8190b9d33f70f8563d61 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.