Triple
T10170879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiamen dialect |
E235327
|
entity |
| Predicate | romanizationSystem |
P6517
|
FINISHED |
| Object |
TLPA
TLPA is a romanization system used to represent the sounds of the Xiamen (Amoy) dialect of Southern Min Chinese using the Latin alphabet.
|
E846023
|
NE FINISHED |
How this triple was built (4 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: [Xiamen dialect, romanizationSystem, TLPA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TLPA Context triple: [Xiamen dialect, romanizationSystem, TLPA]
-
A.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
B.
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.
-
C.
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.
-
D.
LEPA
LEPA is the ICAO airport code for Palma de Mallorca Airport, a major international airport in Spain’s Balearic Islands.
-
E.
TLCP
TLCP is a scholarly law journal focusing on international, transnational, and comparative legal issues.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TLPA Triple: [Xiamen dialect, romanizationSystem, TLPA]
Generated description
TLPA is a romanization system used to represent the sounds of the Xiamen (Amoy) dialect of Southern Min Chinese using the Latin alphabet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TLPA Target entity description: TLPA is a romanization system used to represent the sounds of the Xiamen (Amoy) dialect of Southern Min Chinese using the Latin alphabet.
-
A.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
B.
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.
-
C.
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.
-
D.
LEPA
LEPA is the ICAO airport code for Palma de Mallorca Airport, a major international airport in Spain’s Balearic Islands.
-
E.
TLCP
TLCP is a scholarly law journal focusing on international, transnational, and comparative legal issues.
- F. None of above. chosen
Provenance (5 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9d36608190be78665cc3410cf2 |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300f7aafc8190be874efc755bd188 |
completed | April 6, 2026, 12:40 a.m. |
| NEDg | Description generation | batch_69d30255c7408190a56764f3d3f36ee2 |
completed | April 6, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d30343f4b081909eb80c772f6847bd |
completed | April 6, 2026, 12:50 a.m. |
Created at: March 30, 2026, 9:10 p.m.