Triple
T15775534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annan railway station |
E382479
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Annan |
E304722
|
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: Annan | Statement: [Annan railway station, locatedIn, Annan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annan Context triple: [Annan railway station, locatedIn, Annan]
-
A.
Annan
Annan is the surname of Kofi Annan, the Ghanaian diplomat and former Secretary-General of the United Nations.
-
B.
Annan
chosen
Annan is a small coastal town and former royal burgh in Dumfries and Galloway in southwest Scotland, situated near the mouth of the River Annan.
-
C.
Annan District
Annan District is a coastal urban district in Tainan, Taiwan, known for its wetlands, historical sites, and traditional fishing villages.
-
D.
Vilhelmina
Vilhelmina is a feminine given name of Germanic origin, often associated with royal and noble bearers and used in various European languages.
-
E.
Nayki
Nayki is an island located within Lake Rakshastal in the Tibet Autonomous Region of China.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05198c1588190a65e23c18443eb5c |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877e67b881908a67b9acc79d998f |
completed | May 9, 2026, 7:14 p.m. |
Created at: April 10, 2026, 4:47 a.m.