Triple
T18567388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Fujian dialects |
E453789
|
entity |
| Predicate | hasRomanization |
P2508
|
FINISHED |
| Object | TLPA |
—
|
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: TLPA | Statement: [Southern Fujian dialects, hasRomanization, TLPA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TLPA Context triple: [Southern Fujian dialects, hasRomanization, TLPA]
-
A.
TLPA
chosen
TLPA is a romanization system used to represent the sounds of the Xiamen (Amoy) dialect of Southern Min Chinese using the Latin alphabet.
-
B.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
C.
TPA
TPA is an abbreviation commonly used for a Tri-Party Agreement, a legal contract involving three separate parties that defines their respective rights and obligations.
-
D.
TPA
TPA is the three-letter IATA airport code for Tampa International Airport, a major commercial airport serving the Tampa Bay area in Florida, USA.
-
E.
TLRA
TLRA was the stock ticker symbol for Telaria, a video advertising and monetization technology company that operated a programmatic platform for connected TV and digital video.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53aff027481909ca7257967967650 |
completed | April 19, 2026, 8:28 p.m. |
Created at: April 10, 2026, 11:43 a.m.