Triple
T3002497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northampton |
E81821
|
entity |
| Predicate | historicalMarketTown |
P17485
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Northampton, historicalMarketTown, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalMarketTown Context triple: [Northampton, historicalMarketTown, yes]
-
A.
hasMarketTownHistory
chosen
Indicates that an entity has a historical association with functioning as a market town or possessing recognized market-town status in the past.
-
B.
containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
-
C.
hasHistoricCountySeat
Indicates that an administrative region historically had its county government or main county offices located in a particular settlement or city.
-
D.
hasMarketTownStatus
Indicates that a settlement holds the official legal or historical status of being recognized as a market town.
-
E.
historicalCounty
Indicates that an entity was located within or associated with a county as it existed in the past, even if that county’s boundaries or administrative status have since changed.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a1371c481909e214234afed1a65 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.