Triple
T20188425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Corsair, a Tale |
E492922
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Gulnare |
—
|
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: Gulnare | Statement: [The Corsair, a Tale, mainCharacter, Gulnare]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gulnare Context triple: [The Corsair, a Tale, mainCharacter, Gulnare]
-
A.
Gulnare
chosen
Gulnare is a central female character in Lord Byron’s narrative poem "The Corsair," known for her courage, passion, and pivotal role in the story’s dramatic events.
-
B.
Gul'dan
Gul'dan is a powerful orc warlock and one of the primary antagonists in the Warcraft universe, known for his ruthless pursuit of demonic power and betrayal of his own people.
-
C.
Gülbahar
Gülbahar is the tragic heroine of the Turkish novel "Ağrıdağı Efsanesi," whose love story unfolds against the backdrop of Mount Ararat’s legendary landscape.
-
D.
Gulset
Gulset is a residential district and suburb of the city of Skien in Telemark, Norway.
-
E.
Sahnaya
Sahnaya is a town in southwestern Syria located near Damascus within the Rif Dimashq region.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad2c43c8190a2fc5ef2a0514e53 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.