Triple
T10832895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omar Giménez |
E255667
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Omar |
E93158
|
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: Omar | Statement: [Omar Giménez, hasGivenName, Omar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omar Context triple: [Omar Giménez, hasGivenName, Omar]
-
A.
Omar
chosen
Omar is a masculine given name of Arabic origin meaning "flourishing" or "long-lived," borne by numerous historical and contemporary figures worldwide.
-
B.
Omar
Omar is a critically acclaimed Palestinian thriller film directed by Hany Abu-Assad that explores love, betrayal, and resistance under Israeli occupation.
-
C.
Yahya
Yahya is the Islamic prophet identified with John the Baptist, revered for his piety, asceticism, and role in heralding the coming of Prophet Isa (Jesus).
-
D.
Sallah
Sallah is a jovial, resourceful Egyptian excavator and close ally of Indiana Jones who helps him navigate dangerous archaeological adventures.
-
E.
Mahmoud
Mahmoud is a common Arabic male given name widely used across the Middle East and Muslim-majority countries.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7442439dc8190af59f9c8d0637c01 |
completed | April 9, 2026, 6:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7c739708190b0d58fc2d6392c6c |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:19 p.m.