Triple
T30089915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Lascelles |
E764700
|
entity |
| Predicate | countyAssociatedWith |
P12445
|
FINISHED |
| Object | Yorkshire |
—
|
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: Yorkshire | Statement: [Daniel Lascelles, countyAssociatedWith, Yorkshire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyAssociatedWith Context triple: [Daniel Lascelles, countyAssociatedWith, Yorkshire]
-
A.
cityAssociatedWith
Indicates that there is a notable connection or relationship between a city and another entity, such as relevance, involvement, or contextual association.
-
B.
associatedCityState
Indicates a relationship where a city is linked to the state with which it is formally or contextually connected.
-
C.
capitalCityOfAssociatedState
Indicates that a city serves as the capital of the state with which another entity is associated.
-
D.
regionallyAssociatedWith
chosen
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
E.
cityCounty
Indicates that a city is located within, and administratively belongs to, a specific county.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff49f888348190b9c55afa73b99e6a |
completed | May 9, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69ff49614ef88190ac70b034c55ad738 |
completed | May 9, 2026, 2:49 p.m. |
Created at: April 29, 2026, 7:05 p.m.