Triple
T23385494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mamdouh Habib |
E593865
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Habib |
—
|
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: Habib | Statement: [Mamdouh Habib, familyName, Habib]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Habib Context triple: [Mamdouh Habib, familyName, Habib]
-
A.
Habib
chosen
Habib is a masculine given name of Arabic origin commonly used in North Africa and the Middle East.
-
B.
Hussain
Hussain is a common given name and surname of Arabic origin, widely used in Muslim communities around the world.
-
C.
Abdul
Abdul is a common male given name of Arabic origin meaning "servant of" (typically followed by one of the names of God).
-
D.
Mahbub
Mahbub is a person known primarily through their association with someone named Habib, likely as a relative, close friend, or similarly connected individual.
-
E.
Ahmad
Ahmad is the central protagonist of the story "Man Push Cart," a former Pakistani rock star struggling to make a living as a street vendor in New York City.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a498286c8190abfa381649812cf0 |
completed | April 29, 2026, 6:26 a.m. |
Created at: April 17, 2026, 5:35 p.m.