Triple
T31030250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulster Tower |
E790701
|
entity |
| Predicate | modeledAfterLocatedIn |
P170684
|
FINISHED |
| Object | Clandeboye Estate, County Down |
—
|
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: Clandeboye Estate, County Down | Statement: [Ulster Tower, modeledAfterLocatedIn, Clandeboye Estate, County Down]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeledAfterLocatedIn Context triple: [Ulster Tower, modeledAfterLocatedIn, Clandeboye Estate, County Down]
-
A.
modelingLocation
Indicates the place or setting where the modeling activity or process occurs.
-
B.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
C.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
D.
likelyLocatedIn
Indicates that an entity is probably situated within or associated with a particular location, though not with absolute certainty.
-
E.
modeledInCity
Indicates that an entity (such as a model or design) was created, developed, or constructed within a particular city.
- 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_69f224c97a788190b5da1ead6038a74e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f694c0d90481908afce2e8d6ac0ce3 |
completed | May 3, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 29, 2026, 8:59 p.m.