Triple
T9849696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Royal Green Jackets |
E239432
|
entity |
| Predicate | numberOfRegularBattalionsAtFormation |
P42042
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [The Royal Green Jackets, numberOfRegularBattalionsAtFormation, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegularBattalionsAtFormation Context triple: [The Royal Green Jackets, numberOfRegularBattalionsAtFormation, 3]
-
A.
numberOfBattalions
chosen
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
-
B.
orderOfBattleFeature
Indicates a specific structural or organizational characteristic associated with a military order of battle.
-
C.
hasBattalionNumber
Indicates that an entity (such as a military unit) is associated with a specific battalion number identifier.
-
D.
regimentalCategory
Indicates the classification or type of regiment to which a military unit or formation belongs.
-
E.
militaryFormationOf
Indicates that one entity is a military unit or formation that is organizationally part of, or derived from, another entity.
- F. None of above.
Provenance (3 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb372efc88190a801b2d7384445d7 |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:34 p.m.