Triple
T15800273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N739PA |
E383078
|
entity |
| Predicate | airlineCallsign |
P13478
|
FINISHED |
| Object | CLIPPER |
E424331
|
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: CLIPPER | Statement: [N739PA, airlineCallsign, CLIPPER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLIPPER Context triple: [N739PA, airlineCallsign, CLIPPER]
-
A.
CLIPPER
chosen
CLIPPER was the historic radio callsign used by Pan American World Airways, evoking the airline’s famous flying boat “Clipper” fleet and its pioneering transoceanic services.
-
B.
Clipper
Clipper is a reloadable contactless smart card system used for paying fares on public transit across the San Francisco Bay Area.
-
C.
Clapper
Clapper is the surname of James R. Clapper, the former U.S. Director of National Intelligence and retired Air Force lieutenant general.
-
D.
Cutter
Cutter is a key supporting character in the film "The Prestige," serving as an experienced stage engineer who designs illusions and becomes entangled in the rivalry between two magicians.
-
E.
Cutter
Cutter is a character in the animated series "Monsters at Work," known as a quirky, rule-obsessed monster who works on the facilities team at Monsters, Inc.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4e135b08190b736e77bac5e2bff |
completed | April 16, 2026, 10:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff90b2fd148190b3819d7c41505d52 |
completed | May 9, 2026, 7:53 p.m. |
Created at: April 10, 2026, 4:48 a.m.