Triple
T20688481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Iran |
E508485
|
entity |
| Predicate | officeLocation |
P40
|
FINISHED |
| Object | Pasteur Street, Tehran |
—
|
NE NERFINISHED |
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: Pasteur Street, Tehran | Statement: [President of Iran, officeLocation, Pasteur Street, Tehran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasteur Street, Tehran Context triple: [President of Iran, officeLocation, Pasteur Street, Tehran]
-
A.
Pasteur Street, Tehran
chosen
Pasteur Street in Tehran is a highly secured area that hosts key Iranian government institutions and leadership offices.
-
B.
Hafez Street
Hafez Street is a major north–south thoroughfare in central Tehran, Iran, known for linking key commercial and cultural areas of the city.
-
C.
Ferdowsi Street
Ferdowsi Street is a major thoroughfare in central Tehran, Iran, known for its financial institutions, embassies, and proximity to key cultural and historical sites.
-
D.
Valiasr Street
Valiasr Street is one of Tehran’s main and longest north–south thoroughfares, known as a major commercial and cultural artery of the city.
-
E.
Kargar Street
Kargar Street is a major thoroughfare in Tehran, Iran, known for running through central parts of the city and connecting important academic and commercial areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10b7b808190bdb8b08e53168fb8 |
completed | April 21, 2026, 12:12 a.m. |
Created at: April 16, 2026, 11:49 a.m.