Triple
T13387983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American College for Girls in Istanbul |
E319494
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bebek |
E163551
|
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: Bebek | Statement: [American College for Girls in Istanbul, locatedIn, Bebek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bebek Context triple: [American College for Girls in Istanbul, locatedIn, Bebek]
-
A.
Bebek
chosen
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
-
B.
Bebé
"Bebé" is a track from Ozuna’s hit reggaeton album "Odisea," known for its romantic, melodic style.
-
C.
Bebel
Bebel is the Brazilian-American singer and songwriter Bebel Gilberto, known for her modern bossa nova and electronic-influenced music.
-
D.
Babo
Babo is a central character in Herman Melville’s novella "Benito Cereno," known as the cunning leader of a slave revolt who manipulates appearances aboard a Spanish slave ship.
-
E.
Beba
Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d3a40081909ba49556130ad0e7 |
completed | April 12, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72691c8d08190b971d7e914863cc1 |
completed | May 3, 2026, 10:42 a.m. |
Created at: April 9, 2026, 9:34 p.m.