Triple
T2698708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marine Raiders |
E58576
|
entity |
| Predicate | numberOfBattalions |
P42042
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Marine Raiders, numberOfBattalions, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBattalions Context triple: [Marine Raiders, numberOfBattalions, 4]
-
A.
hasBattalion
Indicates that one entity possesses, commands, or is organizationally assigned a specific battalion.
-
B.
numberOfTroopsInvolved
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
C.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
D.
brigade
Indicates that one entity is organized as, belongs to, or is associated with a military or paramilitary brigade in relation to another entity.
-
E.
garrisonSize
Indicates the number of troops or defenders stationed at a particular location as its garrison.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda339cf48190b9ae6b99137f005e |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd9ceec708190aa162399023b2273 |
completed | March 7, 2026, 7:54 a.m. |
Created at: March 6, 2026, 9:55 p.m.