Triple
T32022178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan and Hubert van Eyck statue |
E817722
|
entity |
| Predicate | locatedInTownTraditionallyAssociatedWith |
P203802
|
FINISHED |
| Object | Jan van Eyck |
E46631
|
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: Jan van Eyck | Statement: [Jan and Hubert van Eyck statue, locatedInTownTraditionallyAssociatedWith, Jan van Eyck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInTownTraditionallyAssociatedWith Context triple: [Jan and Hubert van Eyck statue, locatedInTownTraditionallyAssociatedWith, Jan van Eyck]
-
A.
situatedInTown
Indicates that one entity is located within the geographical or administrative boundaries of a specific town.
-
B.
isInTownKnownFor
Indicates that one entity is located in a town that is notable or distinguished for the other entity.
-
C.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
D.
servesHistoricTown
Indicates that a service, route, or facility provides access or support to a town recognized for its historical significance.
-
E.
locatedInHolyTown
Indicates that an entity is situated within a town that is considered holy or religiously significant.
- F. None of above. chosen
Provenance (5 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_69f348fb04e4819081f4eab040ed7959 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0207a1272c81909dcdb6e3307702f5 |
completed | May 11, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3538ec73d88190951d14c9f0e37ef6 |
completed | June 19, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_6a0205fa1e608190829fd2baa0434fff |
completed | May 11, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_6a0207a073508190adf36e94ab2380ad |
completed | May 11, 2026, 4:45 p.m. |
Created at: May 1, 2026, 12:17 a.m.