Triple
T2016267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Chancellorsville |
E44000
|
entity |
| Predicate | unionStrength |
P34510
|
FINISHED |
| Object | about 130,000 soldiers |
—
|
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 130,000 soldiers | Statement: [Battle of Chancellorsville, unionStrength, about 130,000 soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unionStrength Context triple: [Battle of Chancellorsville, unionStrength, about 130,000 soldiers]
-
A.
UnionStrength
Indicates the degree of solidarity, cohesion, and collective bargaining power within or among unions in a given context.
-
B.
unionStrengthApproximate
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.
-
C.
union
Indicates that two or more sets are combined into a single set containing all elements that belong to at least one of them.
-
D.
laborUnion
Indicates that an entity is a labor union representing workers in collective employment-related matters.
-
E.
associatedWithTradeUnions
Indicates that there is a relationship of involvement, connection, or affiliation between an entity and one or more trade unions.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8cb16048190bc626685fbb5f707 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb83e7888819096dc40275c77daff |
completed | March 7, 2026, 5:31 a.m. |
Created at: March 4, 2026, 7:38 p.m.