Triple
T16625953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Al-Faw |
E403943
|
entity |
| Predicate | commander |
P1061
|
FINISHED |
| Object | Mohsen Rezaee |
E509757
|
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: Mohsen Rezaee | Statement: [Battle of Al-Faw, commander, Mohsen Rezaee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mohsen Rezaee Context triple: [Battle of Al-Faw, commander, Mohsen Rezaee]
-
A.
Mohsen Rezaee
chosen
Mohsen Rezaee is an Iranian politician and former senior military commander who served as the long-time chief of the Islamic Revolutionary Guard Corps during the Iran–Iraq War.
-
B.
Mohsen Foroughi
Mohsen Foroughi was a prominent Iranian architect known for designing significant public and institutional buildings in 20th-century Iran.
-
C.
Ezzatolah Entezami
Ezzatolah Entezami was a highly acclaimed Iranian film and stage actor, widely regarded as one of the most influential and respected figures in the history of Iranian cinema.
-
D.
Mohammad Ali Mojtahedi
Mohammad Ali Mojtahedi was an influential Iranian educator and academic administrator known for his pivotal role in modernizing Iran’s higher education system.
-
E.
Mozaffar Karimi
Mozaffar Karimi is an actor known for his role in the film "Rendition."
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e375530ed081908337dc5c6360d733 |
completed | April 18, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084b7b94481909dfc0dd7b009a5b4 |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:17 a.m.