Triple
T4856210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ares armoured personnel carrier |
E108541
|
entity |
| Predicate | intendedTheatre |
P59969
|
FINISHED |
| Object | high-intensity land warfare |
—
|
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: high-intensity land warfare | Statement: [Ares armoured personnel carrier, intendedTheatre, high-intensity land warfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedTheatre Context triple: [Ares armoured personnel carrier, intendedTheatre, high-intensity land warfare]
-
A.
appliesToTheater
Indicates that something is relevant or applicable specifically to a theater or theatrical context.
-
B.
theater
Indicates that an entity is a theater or is functioning in the role of a theater (a venue where performances or films are shown).
-
C.
servedInTheatre
Indicates that an individual performed military or service duties within a specific theater of operations or geographic area during a conflict or campaign.
-
D.
relatedTheater
Indicates a relationship where one entity is associated with, connected to, or relevant in the context of a particular theater or theatrical venue.
-
E.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:26 p.m.