Triple
T28314643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meis |
E714099
|
entity |
| Predicate | distanceToTurkishCoast_km |
P201289
|
FINISHED |
| Object | about 2 |
—
|
LITERAL 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: about 2 | Statement: [Meis, distanceToTurkishCoast_km, about 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTurkishCoast_km Context triple: [Meis, distanceToTurkishCoast_km, about 2]
-
A.
distanceToTurkishCoast
chosen
Indicates the measured or calculated spatial distance between a given location or object and the coastline of Turkey.
-
B.
distanceToBlackSea
Indicates the measured spatial distance between a given entity and the Black Sea.
-
C.
distanceFromCurrentAralSeaShoreline
Indicates the measured spatial separation between a given location and the present-day shoreline of the Aral Sea.
-
D.
distanceToQatarCoast
Indicates the measured or calculated distance between a given location and the coastline of Qatar.
-
E.
distanceFromSyriaBorder
Indicates the measured spatial separation between a location and the nearest point on Syria’s national border.
- F. None of above.
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_69efb5256afc8190b9322d25c3ae6320 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ffebbd9bac8190b3dca4b7252a2278 |
completed | May 10, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_69ffe93120a08190a44bb64d052eda78 |
completed | May 10, 2026, 2:10 a.m. |
Created at: April 27, 2026, 11:42 p.m.