Triple
T6423458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newport Pagnell |
E127999
|
entity |
| Predicate | hasManufacturingHistory |
P3008
|
FINISHED |
| Object | automobile manufacturing |
—
|
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: automobile manufacturing | Statement: [Newport Pagnell, hasManufacturingHistory, automobile manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManufacturingHistory Context triple: [Newport Pagnell, hasManufacturingHistory, automobile manufacturing]
-
A.
hasHistoricIndustry
chosen
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
B.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
C.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
D.
hasHistoricalOccupationMaterial
Indicates that something is composed of or contains material evidence related to past occupations or uses by people.
-
E.
hadStateOwnershipOfIndustry
Indicates that a governing authority or state entity possessed ownership and control over a particular industry.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06906eea88190a445c1ff1169c2b1 |
completed | March 22, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69c060f780b08190aa650b4d1fc51f21 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:43 p.m.