Triple

T7233337
Position Surface form Disambiguated ID Type / Status
Subject Legislative Palace of Donceles E154955 entity
Predicate namedAfter P63 FINISHED
Object Donceles Street E650480 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: Donceles Street | Statement: [Legislative Palace of Donceles, namedAfter, Donceles Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donceles Street
Context triple: [Legislative Palace of Donceles, namedAfter, Donceles Street]
  • A. Donceles Street chosen
    Donceles Street is a historic thoroughfare in Mexico City’s downtown area, known for its colonial-era architecture, numerous bookstores, and cultural landmarks.
  • B. Rivadavia Street
    Rivadavia Street is a major historic avenue in Buenos Aires, Argentina, running through the city center and several neighborhoods as one of its principal thoroughfares.
  • C. Magallanes Street
    Magallanes Street is a notable thoroughfare in Punta Arenas, Chile, running near the historic Plaza Muñoz Gamero in the city’s center.
  • D. Plateros Street
    Plateros Street was the historic name of a prominent central thoroughfare in Mexico City, later renamed Madero Street.
  • E. Padre Faura Street
    Padre Faura Street is a notable thoroughfare in Manila, Philippines, known for hosting key institutions such as universities, government offices, and commercial establishments.
  • 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea11b03c81909702ad2e0c29758a completed March 27, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d38b5ac4819083837b149ec9e3ea completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:55 p.m.