Triple
T171765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iran |
E3491
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Tehran |
E5216
|
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: Tehran | Statement: [Iran, capital, Tehran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tehran Context triple: [Iran, capital, Tehran]
-
A.
Tehran
chosen
Tehran is the capital and largest city of Iran, serving as the country's political, economic, and cultural center.
-
B.
Baghdad
Baghdad is the capital and largest city of Iraq, historically renowned as a major center of the Islamic Golden Age and a key cultural and economic hub of the Arab world.
-
C.
Istanbul
Istanbul is a transcontinental metropolis straddling Europe and Asia, renowned as Turkey’s cultural and economic hub and for its rich history as the former capital of the Byzantine and Ottoman Empires.
-
D.
Ankara
Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
-
E.
Damascus
Damascus is the capital and one of the largest cities of Syria, renowned as one of the oldest continuously inhabited cities in the world and a historic cultural and commercial center of the Arab world.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a258b94d00819098e90bdfa1306f9f |
completed | Feb. 28, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3161ab0548190b4c0ed74a79cea46 |
completed | Feb. 28, 2026, 4:21 p.m. |
Created at: Feb. 28, 2026, 2:39 a.m.