Triple
T37415481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coalhouse Point |
E929692
|
entity |
| Predicate | nearbyIndustrialHistory |
P199050
|
FINISHED |
| Object | Thames-side forts and batteries |
—
|
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: Thames-side forts and batteries | Statement: [Coalhouse Point, nearbyIndustrialHistory, Thames-side forts and batteries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyIndustrialHistory Context triple: [Coalhouse Point, nearbyIndustrialHistory, Thames-side forts and batteries]
-
A.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
B.
formerIndustrialTown
Indicates that a town previously had a significant industrial base or economy but no longer does.
-
C.
locatedInFormerIndustrialArea
Indicates that an entity is situated within an area that was previously used for industrial purposes but is no longer active as such.
-
D.
foundedAsIndustrialTown
Indicates that a settlement was originally established specifically as an industrial town, typically to support concentrated industrial or manufacturing activity.
-
E.
containsFormerIndustrialAreas
Indicates that an area includes locations that were previously used for industrial purposes but are no longer active industrial sites.
- 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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
| PDg | Predicate description generation | batch_69ff1c90c0f48190a3ede7b36ec77cfd |
completed | May 9, 2026, 11:37 a.m. |
Created at: May 3, 2026, 4:16 p.m.