Triple

T11071716
Position Surface form Disambiguated ID Type / Status
Subject RPLL E261760 entity
Predicate iataCodeForSameAirport P2569 FINISHED
Object MNL E261759 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: MNL | Statement: [RPLL, iataCodeForSameAirport, MNL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MNL
Context triple: [RPLL, iataCodeForSameAirport, MNL]
  • A. MNL chosen
    MNL is the IATA airport code for Ninoy Aquino International Airport, the main international gateway serving Metro Manila in the Philippines.
  • B. Dondon
    Dondon is a historic commune in northern Haiti known for its colonial-era architecture, coffee production, and nearby cave systems with pre-Columbian rock art.
  • C. World Trade Center Metro Manila
    World Trade Center Metro Manila is a major exhibition and convention center in Pasay City that hosts trade shows, conferences, and large-scale events.
  • D. Metro Cebu
    Metro Cebu is the main metropolitan area of Cebu in the Philippines, encompassing Cebu City and its surrounding cities and municipalities as a major economic, cultural, and transportation hub in the Visayas region.
  • E. Santa Mesa, Manila
    Santa Mesa, Manila is a primarily residential and commercial district in the eastern part of Manila, Philippines, known for its dense urban neighborhoods and proximity to major roads and educational institutions.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7994bbb30819090410bd3d0fde33c completed April 9, 2026, 12:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c8bfb0c88190be27f5ce09b02c8b completed April 18, 2026, 6:09 p.m.
Created at: April 8, 2026, 9:26 p.m.