Triple
T11058005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suha Tawil |
E261428
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Suha |
E268768
|
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: Suha | Statement: [Suha Tawil, givenName, Suha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suha Context triple: [Suha Tawil, givenName, Suha]
-
A.
Suha
chosen
Suha is a feminine given name most notably borne by Suha Arafat, the widow of Palestinian leader Yasser Arafat.
-
B.
Suhaila
Suhaila is the young girl protagonist of the children's book "Ladder to the Moon," who embarks on a magical, intergenerational journey with her grandmother to explore themes of compassion and connection.
-
C.
Juwayriya
Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
-
D.
Sharifa
Sharifa is an honorific title used in Islamic tradition for a noblewoman descended from the Prophet Muhammad.
-
E.
Unaizah
Unaizah is a historic oasis city in central Saudi Arabia’s Qassim region, known for its date farms, traditional markets, and cultural heritage.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a2efa48190b290f43dfe836501 |
completed | April 9, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c86e0e6481908f091497313132c1 |
completed | April 18, 2026, 6:07 p.m. |
Created at: April 8, 2026, 9:26 p.m.