Triple
T22238654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thornfield Hall |
E549657
|
entity |
| Predicate | distanceFromGatesheadInFiction |
P146862
|
FINISHED |
| Object | several days’ journey |
—
|
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: several days’ journey | Statement: [Thornfield Hall, distanceFromGatesheadInFiction, several days’ journey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromGatesheadInFiction Context triple: [Thornfield Hall, distanceFromGatesheadInFiction, several days’ journey]
-
A.
distanceToBirkenhead
Indicates the spatial distance between a given entity and the location Birkenhead.
-
B.
distanceFromCastlebay
Indicates the spatial distance between an entity and the location known as Castlebay.
-
C.
distanceFromSunderland
Indicates the spatial distance between a given entity and the location of Sunderland.
-
D.
distanceFromDunkirk
Indicates the spatial distance between a given entity and the location of Dunkirk.
-
E.
distanceFromGiantCauseway
Indicates the measured distance between an entity and the Giant's Causeway.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f132123a048190ba5a90d7acb9aeb2 |
completed | April 28, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69e71b5177d881908f90abde14ada7dc |
completed | April 21, 2026, 6:38 a.m. |
| PDg | Predicate description generation | batch_69e7222e74248190a2d3671049f117f2 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:38 p.m.