Triple
T15156397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaw and Crompton tram stop |
E362088
|
entity |
| Predicate | servesArea |
P82
|
FINISHED |
| Object | Crompton |
E1021532
|
NE 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: Crompton | Statement: [Shaw and Crompton tram stop, servesArea, Crompton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crompton Context triple: [Shaw and Crompton tram stop, servesArea, Crompton]
-
A.
Crompton
Crompton is an English surname most notably associated with Samuel Crompton, the inventor of the spinning mule that revolutionized textile manufacturing during the Industrial Revolution.
-
B.
Crompton
chosen
Crompton is a historic mill village and neighborhood within the town of West Warwick, Rhode Island.
-
C.
Ingersoll
Ingersoll is a small industrial town in southwestern Ontario, Canada, known for its manufacturing sector and proximity to major transportation routes.
-
D.
Eaton’s
Eaton’s was a major Canadian department store chain that became a retail icon and helped shape downtown shopping districts across the country.
-
E.
Seiberling
Seiberling is a surname most notably associated with American industrialist Frank Seiberling, co-founder of the Goodyear Tire & Rubber Company.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060c62b08190bcdbd912d011d1ba |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febff87b6c819097f5cc99b2d75fb6 |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 3:08 a.m.