Triple
T26493801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turner’s Gap |
E669225
|
entity |
| Predicate | hasMilitaryCommanderInvolved |
P42241
|
FINISHED |
| Object | George B. McClellan |
—
|
NE NERFINISHED |
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: George B. McClellan | Statement: [Turner’s Gap, hasMilitaryCommanderInvolved, George B. McClellan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryCommanderInvolved Context triple: [Turner’s Gap, hasMilitaryCommanderInvolved, George B. McClellan]
-
A.
commandersInvolved
chosen
Indicates that specific commanders participated in, oversaw, or were directly involved in a particular event, operation, or engagement.
-
B.
isMilitaryCommand
Indicates that one entity holds formal military authority or command over another entity or group.
-
C.
militaryConflictOversaw
Indicates that one party had authoritative oversight or command responsibility over a military conflict involving another party.
-
D.
battleInvolvedIn
Indicates that an entity participated as a combatant or directly took part in a specific battle or military engagement.
-
E.
wasMilitarized
Indicates that an entity underwent a process of being organized, equipped, or adapted for military use or purposes.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 1:06 a.m.