Triple
T23182458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Square |
E579498
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Square Terminal |
—
|
NE NERFINISHED |
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: [Square, product, Square Terminal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Square Terminal Context triple: [Square, 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 Bordeaux–Mérignac Airport, serving as a key facility for handling flights and travelers at the airport.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f705c14819082c8580a03ed6286 |
completed | April 29, 2026, 4:56 a.m. |
Created at: April 17, 2026, 4:05 p.m.