Triple
T13248892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Sydenham railway station |
E315475
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object | LSY |
E910751
|
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: LSY | Statement: [Lower Sydenham railway station, stationCode, LSY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LSY Context triple: [Lower Sydenham railway station, stationCode, LSY]
-
A.
LSY
chosen
LSY is the three-letter IATA airport code assigned to Lismore Airport in New South Wales, Australia.
-
B.
Lissy
Lissy is a feminine given name, often used as a diminutive or variant of names like Elisabeth or Melissa.
-
C.
NaLyssa
NaLyssa is a professional American basketball player best known for her standout collegiate career at Baylor and subsequent play in the WNBA.
-
D.
Lisea Lyons
Lisea Lyons is an American photographer and artist best known for her 1990s marriage to Green Day drummer Tré Cool.
-
E.
Lisa
Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d9e7ea881908abc4b3a54896692 |
completed | April 10, 2026, 11:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff37f7448190b9c555cae010d3b6 |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:24 p.m.