Triple

T24680591
Position Surface form Disambiguated ID Type / Status
Subject Harvard, Idaho E611117 entity
Predicate distanceToMoscowInMiles P158658 FINISHED
Object about 30 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 30 | Statement: [Harvard, Idaho, distanceToMoscowInMiles, about 30]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: distanceToMoscowInMiles
Context triple: [Harvard, Idaho, distanceToMoscowInMiles, about 30]
  • A. distanceFromMoscow_km
    Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
  • B. railDistanceFromMoscowCenter_km
    Indicates the distance in kilometers from the center of Moscow to a location when traveling by rail.
  • C. distanceToPetersburgInMiles
    Indicates the numerical distance, measured in miles, between a given entity’s location and Petersburg.
  • D. distanceDirectionFromMoscow
    Indicates the relative distance and compass direction of one location measured from Moscow.
  • E. distanceFromSaintPetersburg
    Indicates the spatial distance between a given entity and the city of Saint Petersburg.
  • 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_69e2c4d5c2dc8190ac857dea25ec6ce9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f47b865df48190bf4b6d3e9f9305e6 completed May 1, 2026, 10:08 a.m.
PD Predicate disambiguation batch_69f4682c8a3c8190adbfaac99474eaaf completed May 1, 2026, 8:45 a.m.
PDg Predicate description generation batch_69f47b7f657c81908174590c811a3cbf completed May 1, 2026, 10:07 a.m.
Created at: April 18, 2026, 3:08 a.m.