Triple
T2851774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SeaTac |
E63107
|
entity |
| Predicate | airportCodeServed |
P17503
|
FINISHED |
| Object | SEA |
E180553
|
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: SEA | Statement: [SeaTac, airportCodeServed, SEA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SEA Context triple: [SeaTac, airportCodeServed, SEA]
-
A.
SEA
chosen
SEA is the three-letter IATA airport code for Seattle–Tacoma International Airport, the primary commercial airport serving the Seattle metropolitan area in Washington, USA.
-
B.
SEAQ
SEAQ (Stock Exchange Automated Quotations) was the London Stock Exchange’s electronic quote-driven trading system used primarily for smaller and less liquid securities.
-
C.
SEAS
SEAS is the University of Pennsylvania’s engineering and applied science school, offering undergraduate and graduate programs in fields such as computer science, bioengineering, and mechanical engineering.
-
D.
SEAS
SEAS is the acronym for Yale University's School of Engineering & Applied Science, which houses its engineering and applied science programs.
-
E.
SEAS
SEAS is an abbreviation commonly used to refer to the Seattle Aquarium, a major public aquarium and marine conservation institution located on the waterfront in Seattle, Washington.
- 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_69ab4c407c408190857d25e027155ce9 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf5ca2648190bd32c6ec4b0dd3b6 |
completed | March 7, 2026, 8:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8e4e0b881908de5c4927609725e |
completed | March 10, 2026, 9:48 a.m. |
Created at: March 6, 2026, 10:02 p.m.