Triple
T33265473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thorp Arch |
E851631
|
entity |
| Predicate | hasHistoricalUseNearby |
P51359
|
FINISHED |
| Object | Royal Ordnance Factory Thorp Arch |
—
|
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: Royal Ordnance Factory Thorp Arch | Statement: [Thorp Arch, hasHistoricalUseNearby, Royal Ordnance Factory Thorp Arch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalUseNearby Context triple: [Thorp Arch, hasHistoricalUseNearby, Royal Ordnance Factory Thorp Arch]
-
A.
hasFormerUseNearby
chosen
Indicates that something in the vicinity previously had a particular use or function that is no longer current.
-
B.
hasHistoricalUsageIn
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
C.
hasNearbyHistoricArea
Indicates that one entity is located close to another entity that is designated as a historic area.
-
D.
hasSharedHistoricalUse
Indicates that two or more entities have been used together or in a similar way within the same historical context or period.
-
E.
historicalServiceNear
Indicates that a historical service or event occurred in close spatial proximity to a specified location or entity.
- 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_69f349642dac81908a37ffcc3b976a55 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fec8aef1d8819094c7fd7074038e6b |
completed | May 9, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69fec639876481908efd84a3631a4271 |
completed | May 9, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:32 a.m.