Triple
T13979725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fox Company, 2nd Battalion, 4th Marines |
E336275
|
entity |
| Predicate | standardEquipmentCategory |
P112030
|
FINISHED |
| Object | small arms |
—
|
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: small arms | Statement: [Fox Company, 2nd Battalion, 4th Marines, standardEquipmentCategory, small arms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardEquipmentCategory Context triple: [Fox Company, 2nd Battalion, 4th Marines, standardEquipmentCategory, small arms]
-
A.
standardEquipmentOrigin
Indicates that an item’s standard equipment comes from or is originally supplied by a specified source or origin.
-
B.
primaryEquipment
Indicates that one entity serves as the main or most important piece of equipment used by another entity.
-
C.
uniformCategory
Indicates that two or more entities share the same classification or type within a defined category system.
-
D.
typicalEquipmentLevel
Indicates the usual or standard amount or quality of equipment associated with an entity or situation.
-
E.
standardPar
Indicates that two entities are parallel and conform to a recognized or defined standard of parallelism.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e9fc7248190a9f26e253286ac3c |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:18 p.m.