Triple
T8254118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TransLink |
E193028
|
entity |
| Predicate | rebrandedAs |
P65
|
FINISHED |
| Object | Clipper |
E123351
|
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: [TransLink, rebrandedAs, Clipper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clipper Context triple: [TransLink, rebrandedAs, Clipper]
-
A.
Clipper
chosen
Clipper is a reloadable contactless smart card system used for paying fares on public transit across the San Francisco Bay Area.
-
B.
CLIPPER
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.
-
C.
Corsair
Corsair is a computer hardware and peripherals company best known for its gaming-focused products such as keyboards, mice, headsets, and PC components.
-
D.
Nautica
Nautica is an American lifestyle brand best known for its nautical-inspired apparel and accessories.
-
E.
Clipper Maid of the Seas
Clipper Maid of the Seas was the Boeing 747 aircraft operated by Pan Am that was destroyed in the 1988 Lockerbie bombing of Flight 103.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78f8eccc8190b43204bf2f8defc1 |
completed | March 31, 2026, 7:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd681457908190b39fa034e9ca05d5 |
completed | April 1, 2026, 6:46 p.m. |
Created at: March 30, 2026, 5:48 p.m.