Triple
T18397741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fatma Aliye |
E449911
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Fatma |
—
|
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: Fatma | Statement: [Fatma Aliye, givenName, Fatma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fatma Context triple: [Fatma Aliye, givenName, Fatma]
-
A.
Fatima
Fatima is a renowned Portuguese pilgrimage town famous for reported Marian apparitions and its major Catholic sanctuary.
-
B.
Fatima
Fatima is a small community located on the Magdalen Islands in Quebec, Canada, known for its maritime setting and Acadian culture.
-
C.
Fatima
Fatima is a desert woman in Paulo Coelho’s novel "The Alchemist," symbolizing true love and spiritual devotion that supports the protagonist’s quest.
-
D.
Fatima
chosen
Fatima is a common female given name of Arabic origin, widely used in Muslim-majority cultures and historically associated with Fatimah, the daughter of the Prophet Muhammad.
-
E.
Fatma Mohamed
Fatma Mohamed is an actress best known for her recurring roles in Peter Strickland’s films, including the horror-comedy "In Fabric."
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e5184879548190b7f428e2d4c2caa4 |
completed | April 19, 2026, 6 p.m. |
Created at: April 10, 2026, 10:46 a.m.