Triple
T4817391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Pamplona |
E107620
|
entity |
| Predicate | hasCombatantSide |
P59829
|
FINISHED |
| Object | Spanish forces |
—
|
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: Spanish forces | Statement: [Battle of Pamplona, hasCombatantSide, Spanish forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCombatantSide Context triple: [Battle of Pamplona, hasCombatantSide, Spanish forces]
-
A.
hasOpposingSide
Indicates that one entity possesses or is associated with another entity that lies on the opposite or facing side relative to a reference orientation or boundary.
-
B.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
-
C.
mainCombatant
Indicates that the subject is the primary participant or leading party in a conflict, battle, or combat situation involving the object.
-
D.
hasOpposingFaction
Indicates that one faction stands in opposition or conflict to another faction.
-
E.
hasOpposingFront
Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:24 p.m.