Triple
T20137831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EETN |
E491070
|
entity |
| Predicate | IATACode |
P418
|
FINISHED |
| Object | TLL |
—
|
NE NERFINISHED |
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: TLL | Statement: [EETN, IATACode, TLL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TLL Context triple: [EETN, IATACode, TLL]
-
A.
TLL
chosen
TLL is the three-letter IATA airport code for Lennart Meri Tallinn Airport, the main international airport serving Tallinn, Estonia.
-
B.
Tl
Tl is the official station code used to identify Tiel railway station in the Netherlands.
-
C.
TLT
TLT is the time zone abbreviation used for Timor Leste Time, the standard time observed in East Timor.
-
D.
TLT
TLT is the IATA airport code for the small public airport serving the remote community of Tuluksak in western Alaska.
-
E.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6676879f48190a59da04393d2a8cc |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:32 p.m.