Triple
T36625292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stewart Crossing |
E904152
|
entity |
| Predicate | distanceToMayo_km |
P204971
|
FINISHED |
| Object | approx. 53 |
—
|
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: approx. 53 | Statement: [Stewart Crossing, distanceToMayo_km, approx. 53]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMayo_km Context triple: [Stewart Crossing, distanceToMayo_km, approx. 53]
-
A.
distanceToMoshi
Indicates the spatial distance between a given entity and the location Moshi.
-
B.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
-
C.
distanceFromMahon
Indicates the spatial distance measured from the reference point or location named Mahon to another entity.
-
D.
distanceToMBBAirport_km
Indicates the distance, measured in kilometers, from a given location to the MBB airport.
-
E.
distanceFromHo
Indicates the spatial distance measured from a specified reference point or origin labeled "Ho" to another entity.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:11 p.m.