Triple
T4187271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 7th Battalion, Green Howards |
E88341
|
entity |
| Predicate | hasBattalionNumber |
P54534
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [7th Battalion, Green Howards, hasBattalionNumber, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBattalionNumber Context triple: [7th Battalion, Green Howards, hasBattalionNumber, 7]
-
A.
hasBattalion
Indicates that one entity possesses, commands, or is organizationally assigned a specific battalion.
-
B.
numberOfBattalions
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
-
C.
regimentalNumber
Indicates the unique identifying number assigned to a member of a regiment, linking an individual to their specific regimental record.
-
D.
hasMilitaryDivision
Indicates that an entity possesses, includes, or is organizationally associated with a specific military division.
-
E.
brigade
Indicates that one entity is organized as, belongs to, or is associated with a military or paramilitary brigade in relation to another entity.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af04b009dc8190abda3f149a5b16fa |
completed | March 9, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69af01935064819096b7619f42e164dd |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af04af4e44819098a9d7f91e65adf2 |
completed | March 9, 2026, 5:34 p.m. |
Created at: March 9, 2026, 3:45 p.m.