Triple

T6274429
Position Surface form Disambiguated ID Type / Status
Subject Block, Inc. E140619 entity
Predicate product P490 FINISHED
Object Square Terminal E579501 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: Square Terminal | Statement: [Block, Inc., product, Square Terminal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Square Terminal
Context triple: [Block, Inc., product, Square Terminal]
  • A. Square Terminal chosen
    Square Terminal is a portable, all-in-one point-of-sale device designed by Square for businesses to accept card payments and manage transactions.
  • B. Terminal B
    Terminal B is one of the two main passenger terminals at Hollywood Burbank Airport, serving commercial airline flights in the Burbank–Los Angeles area.
  • C. Terminal B
    Terminal B is one of the passenger terminals at George Bush Intercontinental Airport in Houston, primarily serving domestic flights and regional operations.
  • D. Terminal B
    Terminal B is one of the passenger terminals at Vnukovo International Airport in Moscow, serving as a key facility for handling flights and travelers.
  • E. Terminal B
    Terminal B is one of the main passenger terminals at Boston Logan International Airport, serving numerous domestic and some international flights with multiple airlines.
  • 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_69c008cc158881908df6ec94a911c736 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063c0629c8190805ddf1a604e9ca4 completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c519404dbc8190850f7874d2be51b5 completed March 26, 2026, 11:32 a.m.
Created at: March 22, 2026, 4:25 p.m.