Triple
T17154598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawar Islands |
E416310
|
entity |
| Predicate | distanceToMainBahrainIsland |
P126325
|
FINISHED |
| Object | approximately 20 kilometers or more |
—
|
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: approximately 20 kilometers or more | Statement: [Hawar Islands, distanceToMainBahrainIsland, approximately 20 kilometers or more]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMainBahrainIsland Context triple: [Hawar Islands, distanceToMainBahrainIsland, approximately 20 kilometers or more]
-
A.
distanceFromDohaCenter
Indicates the spatial distance between a given location and the central point of Doha.
-
B.
distanceFromAjmanCity
Indicates the measured spatial distance separating a given location from Ajman City.
-
C.
distanceToMuscat
Indicates the measured or calculated distance between a given entity’s location and the city of Muscat.
-
D.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
E.
distanceFromDoha
Indicates the spatial distance between a given location or entity and the city of Doha.
- F. None of above. chosen
Provenance (4 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f40a6b7c8190838e588c4fd81d95 |
completed | April 18, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:37 a.m.