Triple
T26492894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colsterworth |
E669204
|
entity |
| Predicate | nearbyHamlet |
P61362
|
FINISHED |
| Object | Woolsthorpe-by-Colsterworth |
—
|
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: Woolsthorpe-by-Colsterworth | Statement: [Colsterworth, nearbyHamlet, Woolsthorpe-by-Colsterworth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyHamlet Context triple: [Colsterworth, nearbyHamlet, Woolsthorpe-by-Colsterworth]
-
A.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
-
B.
meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
-
C.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
D.
nearbyHunebed
Indicates that one entity is located close to a hunebed (a megalithic stone tomb), within a short spatial distance.
-
E.
nearestHut
Indicates that one hut is the closest in distance to a given reference point or entity compared to all other huts.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 27, 2026, 1:05 a.m.