Triple
T32565520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quartz Hill |
E832351
|
entity |
| Predicate | distanceToLosAngelesInMiles |
P19368
|
FINISHED |
| Object | about 70 |
—
|
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: about 70 | Statement: [Quartz Hill, distanceToLosAngelesInMiles, about 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLosAngelesInMiles Context triple: [Quartz Hill, distanceToLosAngelesInMiles, about 70]
-
A.
distanceToLosAngeles
chosen
Indicates the measured or calculated distance between a given entity’s location and the city of Los Angeles.
-
B.
distanceFromLosAngeles
Indicates the measured or specified distance between a given entity’s location and the city of Los Angeles.
-
C.
distanceToCali
Indicates the measured or estimated distance between an entity and the location referred to as Cali.
-
D.
distanceToSanDiego
Indicates the measured or estimated distance between a given entity’s location and the city of San Diego.
-
E.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
- 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_69f34927bb308190ad94da1b11cad13c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:03 a.m.