Triple
T20818740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Massoud Amir Behrani |
E512513
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Massoud |
—
|
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: Massoud | Statement: [Colonel Massoud Amir Behrani, givenName, Massoud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Massoud Context triple: [Colonel Massoud Amir Behrani, givenName, Massoud]
-
A.
Massoud
chosen
Massoud is a surname most notably associated with Mena Massoud, the Egyptian-Canadian actor who starred as Aladdin in Disney’s live-action adaptation.
-
B.
Daoud
Daoud is the middle name of Egyptian-born American engineer and academic administrator Daoud Dean.
-
C.
Daoud
Daoud is a rapper and producer known for his work with the Chicago-based hip-hop collective Pivot Gang.
-
D.
Amrullah
Amrullah is an Afghan politician and former intelligence chief who served as Vice President of Afghanistan and became a prominent opponent of the Taliban.
-
E.
Khader Khan
Khader Khan is a powerful and charismatic Mumbai mafia don and philosophical mentor figure in Gregory David Roberts’ novel *Shantaram*.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f5b1e08190a9c26f76bd544b68 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.