Triple
T27826698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harthill Services |
E702972
|
entity |
| Predicate | betweenCities |
P163389
|
FINISHED |
| Object | Edinburgh |
—
|
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: Edinburgh | Statement: [Harthill Services, betweenCities, Edinburgh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: betweenCities Context triple: [Harthill Services, betweenCities, Edinburgh]
-
A.
betweenCities
chosen
Indicates a relationship where something is located or occurs in the space or context separating two specified cities.
-
B.
betweenCity
Indicates a spatial relationship where one entity is located in the area or position separating two specified cities.
-
C.
cityRelationship
Indicates a relationship that specifies how one city is connected or related to another city (e.g., administratively, geographically, or functionally).
-
D.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
-
E.
distanceBetweenHomeCities
Indicates the measured spatial distance separating the home cities of two entities.
- 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_69ef840ad1e88190b5bff2d1ddec8700 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 5:52 p.m.