Triple
T7504046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of South Mountain |
E177339
|
entity |
| Predicate | unionStrengthApprox |
P26187
|
FINISHED |
| Object | about 28,000–30,000 troops |
—
|
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: about 28,000–30,000 troops | Statement: [Battle of South Mountain, unionStrengthApprox, about 28,000–30,000 troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unionStrengthApprox Context triple: [Battle of South Mountain, unionStrengthApprox, about 28,000–30,000 troops]
-
A.
unionStrengthApproximate
chosen
Indicates that the strength of a union or combination between entities is represented in an estimated or approximate manner rather than as an exact value.
-
B.
unionStrength
Indicates the degree of solidarity, cohesion, or collective power within or among unions or union members.
-
C.
UnionStrength
Indicates the degree of solidarity, cohesion, and collective bargaining power within or among unions in a given context.
-
D.
UnionForcesStrength
Indicates the level or magnitude of military power possessed by Union forces in a given context.
-
E.
union
Indicates that two or more sets are combined into a single set containing all elements that belong to at least one of them.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:44 p.m.