Triple
T29043288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Squirrel |
E738057
|
entity |
| Predicate | relatesToManufacturer |
P4022
|
FINISHED |
| Object | Airbus Helicopters |
—
|
NE NERFINISHED |
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: Airbus Helicopters | Statement: [Squirrel, relatesToManufacturer, Airbus Helicopters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatesToManufacturer Context triple: [Squirrel, relatesToManufacturer, Airbus Helicopters]
-
A.
usedManufacturer
Indicates that an entity has employed or sourced products, components, or services from a particular manufacturer.
-
B.
alsoManufacturedBy
Indicates that an item or product is produced by an additional manufacturer beyond the primary or previously mentioned one.
-
C.
manufacturedBy
chosen
Indicates that an item or product is produced or created by a specific manufacturer or maker.
-
D.
relatedToProduct
Indicates a general association or connection between an entity and a specific product, without specifying the exact nature of that relationship.
-
E.
usedByManufacturer
Indicates that a manufacturer makes use of a particular resource, component, method, or tool in its production or operational processes.
- 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_69f077efb3848190b41574e1670f6ae2 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a00b3d2e0c88190a8bf49576e654f64 |
completed | May 10, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_6a00b376f4e48190a6676779fe02ea9f |
completed | May 10, 2026, 4:33 p.m. |
Created at: April 28, 2026, 10:03 a.m.