Triple
T17255315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WSSS |
E418864
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | SIN |
E418863
|
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: SIN | Statement: [WSSS, IATAcode, SIN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SIN Context triple: [WSSS, IATAcode, SIN]
-
A.
SIN
chosen
SIN is the IATA airport code for Singapore Changi Airport, the main international gateway to Singapore and one of the world’s busiest and most acclaimed airports.
-
B.
SINP
SINP is the commonly used abbreviation for the Skobeltsyn Institute of Nuclear Physics, a major Russian research institute specializing in nuclear and particle physics.
-
C.
Sines
Sines is a coastal town in Portugal known as the birthplace of the famed explorer Vasco da Gama.
-
D.
Sinn
Sinn is Gottlob Frege’s notion of “sense,” the mode of presentation through which a linguistic expression conveys its reference and cognitive significance.
-
E.
Sinn
Sinn is a river in northern Bavaria, Germany, that flows through the Lower Franconia region.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6c362c819088965c6e05f33faf |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170fd7f7c81908f417fa758e861a2 |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.