Triple

T16165334
Position Surface form Disambiguated ID Type / Status
Subject Hisar Airport E392288 entity
Predicate serves P98 FINISHED
Object Hisar E389632 NE 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: Hisar | Statement: [Hisar Airport, serves, Hisar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hisar
Context triple: [Hisar Airport, serves, Hisar]
  • A. Hisar chosen
    Hisar is a major city in the Indian state of Haryana known for its historical significance, agricultural research institutions, and role as a regional commercial center.
  • B. Hisarlik
    Hisarlik is an archaeological mound in northwestern Turkey widely identified as the site of ancient Troy, extensively excavated by Heinrich Schliemann.
  • C. Qalat
    Qalat is a key urban center and provincial capital in southern Afghanistan, known for its strategic location and historical fortifications.
  • D. Bala Hissar
    Bala Hissar is the elevated citadel area of Golconda Fort in Hyderabad, historically serving as its royal and defensive stronghold.
  • E. Uçhisar
    Uçhisar is a small town in Turkey’s Cappadocia region, best known for its towering rock castle and panoramic views over the surrounding fairy-chimney landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21eb2a25c819095437b25e6ab83f3 completed April 17, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00456f2ba481909f243ab2c4619623 completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:02 a.m.