Triple
T8159906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iran Aseman Airlines |
E190548
|
entity |
| Predicate | hasFocusCity |
P1295
|
FINISHED |
| Object | Isfahan |
E68692
|
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: Isfahan | Statement: [Iran Aseman Airlines, hasFocusCity, Isfahan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isfahan Context triple: [Iran Aseman Airlines, hasFocusCity, Isfahan]
-
A.
Isfahan
chosen
Isfahan is a historic Iranian city renowned for its Safavid-era architecture, grand mosques, and role as a major political and cultural center in early modern Persia.
-
B.
Mashhad
Mashhad is a major city in northeastern Iran renowned as a leading religious and cultural center of the Islamic world, centered around the shrine of Imam Reza.
-
C.
شیراز
شیراز یکی از مهمترین و تاریخیترین شهرهای ایران است که بهعنوان مرکز فرهنگ، ادب و شعر فارسی شناخته میشود.
-
D.
Kashan
Kashan is an Iranian city renowned for its rich history, traditional architecture, and production of high-quality Persian carpets.
-
E.
Hamadan
Hamadan is an ancient city in western Iran, historically significant as a major center of Persian Jewish life and one of the oldest continuously inhabited cities in the region.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb45537d248190a0e998b6d336e6e1 |
completed | March 31, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce88498cf081909c25c292c014fe8c |
completed | April 2, 2026, 3:16 p.m. |
Created at: March 30, 2026, 5:38 p.m.