Triple
T13288164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Red-Haired Woman |
E316494
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Cem |
E676004
|
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: Cem | Statement: [The Red-Haired Woman, hasCharacter, Cem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cem Context triple: [The Red-Haired Woman, hasCharacter, Cem]
-
A.
Cem
chosen
Cem is a masculine given name of Turkish origin, commonly used in Turkey and among Turkish communities worldwide.
-
B.
Halil
Halil is the given name of Çandarlı Halil Pasha, a prominent Ottoman statesman and grand vizier in the 15th century.
-
C.
Mahmut
Mahmut is a masculine given name commonly used in Turkish and related cultures, derived from the Arabic name Mahmoud.
-
D.
Kadir
Kadir is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
-
E.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99076aeec8190b0cb883ab60d3f6b |
completed | April 11, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716d4a6f48190a2020e11e887be2e |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:27 p.m.