Triple
T26686712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5th New York Infantry (Duryee’s Zouaves) |
E672765
|
entity |
| Predicate | initialCommanderRank |
P165050
|
FINISHED |
| Object | colonel |
—
|
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: colonel | Statement: [5th New York Infantry (Duryee’s Zouaves), initialCommanderRank, colonel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialCommanderRank Context triple: [5th New York Infantry (Duryee’s Zouaves), initialCommanderRank, colonel]
-
A.
hasCommanderRank
Indicates that an entity holds the military or organizational rank of commander within a specified hierarchy or context.
-
B.
commanderInChiefRank
Indicates that an entity holds the highest-ranking leadership position over a military or armed forces organization.
-
C.
commandingOfficerRank
Indicates the military rank held by the officer who has command authority over a given individual or unit.
-
D.
governmentCommanderRank
Indicates that an individual holds a specific rank within a government’s command or leadership hierarchy.
-
E.
opposingCommanderRank
Indicates that the related entity holds a specific military rank as the commander of the opposing or enemy force in a conflict or engagement.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 27, 2026, 3:23 a.m.