Triple
T6474295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of El Caney |
E146030
|
entity |
| Predicate | combatantsNationality |
P71123
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Battle of El Caney, combatantsNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatantsNationality Context triple: [Battle of El Caney, combatantsNationality, American]
-
A.
combatantsIncluded
Indicates that the specified entities are participants or parties involved in a particular combat or conflict.
-
B.
combatantCulture1
Indicates that the first combatant in a conflict is associated with a particular culture or cultural group.
-
C.
combatantCulture2
Indicates the cultural or ethnic background of the second party involved in a combat or conflict relationship.
-
D.
opponentNationality
Indicates that the related entity is the country or nationality of the opponent in a competitive or adversarial context.
-
E.
countryDuringBattle
Indicates that a specified country was involved in or existed as a relevant participant or context during a particular battle.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a32c0188190bcb3c35fc1d796a6 |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c06822f73081908e6bb9edecbe77a6 |
completed | March 22, 2026, 10:07 p.m. |
Created at: March 22, 2026, 4:50 p.m.