Triple
T22658384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phanar Greek Orthodox High School |
E559292
|
entity |
| Predicate | quarter |
P23240
|
FINISHED |
| Object | Fener |
—
|
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: Fener | Statement: [Phanar Greek Orthodox High School, quarter, Fener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fener Context triple: [Phanar Greek Orthodox High School, quarter, Fener]
-
A.
Fener
chosen
Fener is a historic neighborhood in Istanbul, Turkey, known for its Greek Orthodox heritage and landmarks such as the Ecumenical Patriarchate and traditional Ottoman-era houses.
-
B.
Fenadi
Fenadi is a cultural festival held in Ijuí, Brazil, celebrating the traditions and heritage of the region’s diverse immigrant communities.
-
C.
Ferizli
Ferizli is a town and district located in Sakarya Province in the Marmara Region of northwestern Turkey.
-
D.
Fasa
Fasa is a city in Iran’s Fars Province known as a regional agricultural and commercial center with historical significance.
-
E.
Feresten
Feresten is the surname of Spike Feresten, an American television writer, comedian, and talk show host known for his work on shows like Seinfeld and Late Show with David Letterman.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765d10588190b4574f3e64617cd4 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:07 p.m.