Triple
T7433752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Calder |
E171555
|
entity |
| Predicate | distanceToLivingston |
P76378
|
FINISHED |
| Object | approximately 3 miles east |
—
|
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 3 miles east | Statement: [East Calder, distanceToLivingston, approximately 3 miles east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLivingston Context triple: [East Calder, distanceToLivingston, approximately 3 miles east]
-
A.
distanceFromDallas
Indicates the measured distance between a given place or entity and the city of Dallas.
-
B.
distanceToMontgomery
Indicates the spatial distance between a given entity and the location identified as Montgomery.
-
C.
distanceToStLouis
Indicates the measured distance between a given entity’s location and the city of St. Louis.
-
D.
distanceToPittsburgh
Indicates the spatial distance between a given entity’s location and the city of Pittsburgh.
-
E.
distanceToLancaster
Indicates the measured distance between a given entity’s location and the location of Lancaster.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f327480481909c4691fd3333e2ae |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0be2b1c8190bea06100a7caef2b |
completed | March 27, 2026, 9:03 p.m. |
Created at: March 27, 2026, 3:12 p.m.