Triple
T20481443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tadj ol-Molouk |
E502462
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Malakeh-ye Madar |
—
|
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: Malakeh-ye Madar | Statement: [Tadj ol-Molouk, title, Malakeh-ye Madar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malakeh-ye Madar Context triple: [Tadj ol-Molouk, title, Malakeh-ye Madar]
-
A.
Kalaleh
Kalaleh is a city in northeastern Iran known as a local administrative and agricultural center.
-
B.
Zal-e Zar
Zal-e Zar is a legendary white-haired hero and prince in the Persian epic Shahnameh, renowned for his wisdom, bravery, and role as the father of the champion Rostam.
-
C.
Malakeh-ye Irān
chosen
Malakeh-ye Irān is the Persian title historically used to refer to the queen consort of Iran.
-
D.
Aghbalou
Aghbalou is a small village in Morocco’s Ourika Valley, known for its scenic mountain setting and traditional Berber character.
-
E.
Negahban
Negahban is the surname of Navid Negahban, an Iranian-American actor known for his roles in film and television, including the series "Homeland."
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b56dd248190b6bc4e513aff3c9c |
completed | April 20, 2026, 9:32 p.m. |
Created at: April 16, 2026, 11:34 a.m.