Triple
T2991578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoogali |
E80765
|
entity |
| Predicate | distanceToGriffith |
P44559
|
FINISHED |
| Object | approximately a few kilometres |
—
|
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 a few kilometres | Statement: [Yoogali, distanceToGriffith, approximately a few kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGriffith Context triple: [Yoogali, distanceToGriffith, approximately a few kilometres]
-
A.
distanceFromGori
Indicates the spatial distance between a given entity or location and the place named Gori.
-
B.
distanceToBingham
Indicates the measured or calculated distance between a given entity and the location named Bingham.
-
C.
distanceToBawtry
Indicates the spatial distance between a given entity and the location of Bawtry.
-
D.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
E.
distanceFromReading
Indicates the measured spatial distance between a specified entity and the location of Reading.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99df69d08190a0e25efb0dc8d653 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad961403108190bbecb8d3608fd4e0 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:59 p.m.