Triple

T6674521
Position Surface form Disambiguated ID Type / Status
Subject Sa el-Hagar E151816 entity
Predicate nearbyCity P350 FINISHED
Object Tanta E46653 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: Tanta | Statement: [Sa el-Hagar, nearbyCity, Tanta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanta
Context triple: [Sa el-Hagar, nearbyCity, Tanta]
  • A. Tanta chosen
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • B. Tanta
    Tanta is a small Andean town in Peru known for its high-altitude landscapes and traditional rural life within the Nor Yauyos-Cochas scenic reserve.
  • C. Ismailia
    Ismailia is a city in northeastern Egypt on the west bank of the Suez Canal, known for its strategic location, colonial-era architecture, and role as an administrative center for the canal zone.
  • D. سوسة
    سوسة هي مدينة ساحلية تونسية تاريخية على البحر الأبيض المتوسط تشتهر بمدينتها العتيقة المصنفة ضمن مواقع التراث العالمي.
  • E. Ras Lanuf
    Ras Lanuf is a major oil port and industrial town on Libya’s Mediterranean coast, known for its large refinery and strategic role in the country’s petroleum exports.
  • 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_69c687f830bc81909eb8b04dbb8450b1 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0f1d9d081909670f5c0b7389c0d completed March 27, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7a30b7481908c36ff9035f62731 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:03 p.m.