Triple
T30975886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. 94th Infantry Division |
E789229
|
entity |
| Predicate | notableOperationsArea |
P52790
|
FINISHED |
| Object | France |
E861
|
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: France | Statement: [U.S. 94th Infantry Division, notableOperationsArea, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableOperationsArea Context triple: [U.S. 94th Infantry Division, notableOperationsArea, France]
-
A.
notableOperationArea
chosen
Indicates the geographic area or region where an entity primarily conducts or is recognized for its significant operations or activities.
-
B.
notableProjectArea
Indicates that an entity has a significant or distinguished project specifically associated with a particular area or domain.
-
C.
notableTargetArea
Indicates that an action, effect, or focus is specifically directed toward a particularly important or prominent area or region.
-
D.
notableWorkArea
Indicates the field or domain in which an entity’s significant work or contributions are primarily focused.
-
E.
notableExceptionArea
Indicates that a specific area is recognized as an exception to a general rule, pattern, or classification that applies elsewhere.
- 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_69f224c4831c8190be53924ec25a150a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a28fba4d3e48190a2c2729b968d8e9a |
completed | June 10, 2026, 5:52 a.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:55 p.m.