Triple

T15703407
Position Surface form Disambiguated ID Type / Status
Subject Dagan E380648 entity
Predicate worshipPlace P1191 FINISHED
Object Terqa E1171869 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: Terqa | Statement: [Dagan, worshipPlace, Terqa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terqa
Context triple: [Dagan, worshipPlace, Terqa]
  • A. Terqa chosen
    Terqa was an ancient Mesopotamian city on the middle Euphrates, serving as a regional political and commercial center in what is now eastern Syria.
  • B. Taza
    Taza was a 19th-century Apache leader and the son of the famous chief Cochise, known for succeeding his father as a chief of the Chiricahua Apache.
  • C. Taza
    Taza is a historic city in northern Morocco known for its strategic location between the Rif and Middle Atlas mountains and its role as a key passage linking eastern and western Morocco.
  • D. Kerketeas
    Kerketeas is a prominent mountain on the Greek island of Samos, known for its rugged terrain and significant elevation.
  • E. Mengistu
    Mengistu is a male given name of Ethiopian origin, notably borne by several prominent Ethiopian political and military figures.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f6e965881909319f85c51c6fb74 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f05d648190a0c73b60dc027287 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:45 a.m.