Triple
T584550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Pork Chop Hill |
E15129
|
entity |
| Predicate | engagementCharacteristic |
P662
|
FINISHED |
| Object | night assaults |
—
|
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: night assaults | Statement: [Battle of Pork Chop Hill, engagementCharacteristic, night assaults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagementCharacteristic Context triple: [Battle of Pork Chop Hill, engagementCharacteristic, night assaults]
-
A.
engagementType
Indicates the specific kind or category of engagement or interaction that occurs between the related entities.
-
B.
engagementLevel
Indicates the degree or intensity of involvement, interest, or participation one entity has in relation to another entity, activity, or context.
-
C.
notableEngagement
Indicates a significant interaction, involvement, or participation between entities that is noteworthy or distinguished in some context.
-
D.
engagementArea
Indicates the spatial region or scope within which an entity’s actions, influence, or interactions are intended to occur.
-
E.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9874c88190bd1e08d4689ea124 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.