Triple
T986789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persian Corridor |
E21296
|
entity |
| Predicate | keyRailHub |
P523
|
FINISHED |
| Object | Bandar Shah |
E116619
|
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: Bandar Shah | Statement: [Persian Corridor, keyRailHub, Bandar Shah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bandar Shah Context triple: [Persian Corridor, keyRailHub, Bandar Shah]
-
A.
Bandar Shahpur
chosen
Bandar Shahpur is a port city in southwestern Iran on the Persian Gulf that historically served as a key maritime and logistical hub, including during World War II supply routes.
-
B.
Nasirabad
Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
-
C.
Kota
Kota is a major industrial and educational city in southeastern Rajasthan, India, known for its coaching institutes and power plants along the Chambal River.
-
D.
Gwadar
Gwadar is a strategic deep-sea port city in southwestern Pakistan that serves as a key maritime hub on the Arabian Sea and a central component of the China–Pakistan Economic Corridor.
-
E.
Mardan
Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b75103688190a14342eef3842984 |
completed | March 1, 2026, 10:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a1684ac8190952d7143fe9a5e7f |
completed | March 7, 2026, 1:37 p.m. |
Created at: March 1, 2026, 7:41 p.m.