Triple
T24919040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stamullen |
E624068
|
entity |
| Predicate | distanceToDublinCityCentre_km |
P26819
|
FINISHED |
| Object | approximately 35 |
—
|
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: approximately 35 | Statement: [Stamullen, distanceToDublinCityCentre_km, approximately 35]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDublinCityCentre_km Context triple: [Stamullen, distanceToDublinCityCentre_km, approximately 35]
-
A.
distanceFromDublinCityCentre_km
chosen
Indicates the physical distance, measured in kilometers, between an entity’s location and the center of Dublin city.
-
B.
distanceFromCorkCity
Indicates the spatial distance between a given place and Cork City.
-
C.
distanceFromGalway
Indicates the spatial distance separating an entity from the location of Galway.
-
D.
distanceToTullamore_km
Indicates the physical distance, measured in kilometers, between a given location and Tullamore.
-
E.
distanceToDungannon_km
Indicates the distance, measured in kilometers, between a given entity’s location and Dungannon.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 18, 2026, 5:28 a.m.