Triple
T1975790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SETSqx |
E42907
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | SEAQ |
E223470
|
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: SEAQ | Statement: [SETSqx, relatedTo, SEAQ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SEAQ Context triple: [SETSqx, relatedTo, SEAQ]
-
A.
SEAQ
chosen
SEAQ (Stock Exchange Automated Quotations) was the London Stock Exchange’s electronic quote-driven trading system used primarily for smaller and less liquid securities.
-
B.
SEA
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.
-
C.
SEAS
SEAS is the acronym for Yale University's School of Engineering & Applied Science, which houses its engineering and applied science programs.
-
D.
SavU Sea
The Savu Sea is a small sea in the western Pacific Ocean, located between the Indonesian islands of Sumba, Timor, and Flores, known for its deep waters and rich marine biodiversity.
-
E.
Seascape
Seascape is a Pulitzer Prize-winning play by Edward Albee that blends domestic drama with surreal encounters between humans and evolved sea creatures to explore themes of communication, evolution, and aging.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f835108190b0709ccf3a487a96 |
completed | March 7, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0acfce948190bb714023b6dab9ed |
completed | March 8, 2026, 11:48 p.m. |
Created at: March 4, 2026, 7:36 p.m.