Triple
T32775171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kershaw’s Brigade marker |
E838178
|
entity |
| Predicate | associatedWithArmy |
P126571
|
FINISHED |
| Object | Army of Northern Virginia |
E23941
|
NE 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: Army of Northern Virginia | Statement: [Kershaw’s Brigade marker, associatedWithArmy, Army of Northern Virginia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithArmy Context triple: [Kershaw’s Brigade marker, associatedWithArmy, Army of Northern Virginia]
-
A.
appliedToArmy
Indicates that something (such as a policy, strategy, or resource) is directed toward, implemented for, or used in relation to an army.
-
B.
associatedWithWar
Indicates a relationship where an entity is connected or related to war, such as by involvement, influence, cause, or context.
-
C.
servedArmy
chosen
Indicates that an entity has performed military service in, or been a member of, a particular army.
-
D.
associatedWithBattle
Indicates a relationship where an entity is connected or linked to a specific battle, such as by participation, relevance, or involvement.
-
E.
mentionsArmy
Indicates that one entity explicitly refers to or brings up an army in relation to another entity.
- F. None of above.
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_69f3493a824c8190938489ba69041d08 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34bceb22cc8190be7b2ef983864590 |
completed | June 19, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:13 a.m.