Triple
T7806046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SEA |
E180553
|
entity |
| Predicate | associatedWithFAAIdentifier |
P420
|
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: [SEA, associatedWithFAAIdentifier, SEA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SEA Context triple: [SEA, associatedWithFAAIdentifier, SEA]
-
A.
SEA
SEA is the high-speed rail line designation used for the LGV Sud Europe Atlantique route in France.
-
B.
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.
-
C.
SEA
SEA is the commonly used abbreviation for the Single European Act, a landmark 1986 treaty that significantly advanced European Community integration and paved the way for the single market.
-
D.
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.
-
E.
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.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf63838b88190a085756db9ca25c4 |
completed | March 30, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14439c8081908331caf450462a0e |
completed | March 31, 2026, 12:24 a.m. |
Created at: March 30, 2026, 4:35 p.m.