Triple
T1093688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northrop Grumman |
E24222
|
entity |
| Predicate | servesMarket |
P2193
|
FINISHED |
| Object | military |
—
|
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: military | Statement: [Northrop Grumman, servesMarket, military]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesMarket Context triple: [Northrop Grumman, servesMarket, military]
-
A.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
B.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
-
C.
isServed
Indicates that one entity provides or delivers a service, product, or assistance to another entity.
-
D.
sectorServed
chosen
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
E.
marketedFor
Indicates that something is promoted, advertised, or positioned as being intended or suitable for a particular use, audience, or purpose.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99d1e8c81909cf1178d68d38885 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.