Triple
T8656939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selamlık |
E205442
|
entity |
| Predicate | contrastedWith |
P278
|
FINISHED |
| Object | Harem |
E163541
|
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: Harem | Statement: [Selamlık, contrastedWith, Harem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harem Context triple: [Selamlık, contrastedWith, Harem]
-
A.
Harem
"Harem" is a song by the American rock band War from their album "War & Leisure."
-
B.
Imperial Harem
chosen
The Imperial Harem was the secluded residential and administrative quarters of the Ottoman sultans’ wives, concubines, and female relatives, serving as a powerful political and social center within the Topkapi Palace.
-
C.
Mezallat
Mezallat is a passenger station on Cairo Metro’s Line 2 serving commuters in the Greater Cairo area.
-
D.
Thousand & One
Thousand & One is a prominent Class A office tower within the Water Street Tampa development, known for its modern design and premium commercial workspace.
-
E.
Ombre sultane
Ombre sultane is a novel by Algerian writer Assia Djebar that explores women’s voices, memory, and identity in a postcolonial North African context.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484569788190aa41395854684e6f |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccec941881908263cd3205f10ccd |
completed | April 2, 2026, 8:09 p.m. |
Created at: March 30, 2026, 6:30 p.m.