Triple
T4736647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greek mythology |
E105140
|
entity |
| Predicate | hasConcept |
P531
|
FINISHED |
| Object | Fates |
E156160
|
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: Fates | Statement: [Greek mythology, hasConcept, Fates]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fates Context triple: [Greek mythology, hasConcept, Fates]
-
A.
Fates
chosen
The Fates are the three ancient Greek goddesses who control the destiny and lifespan of every mortal and god.
-
B.
Fate to Fatal
"Fate to Fatal" is an EP by American alternative rock band The Breeders, showcasing their lo-fi indie sound in a short collection of tracks released in the late 2000s.
-
C.
The Fourmost
The Fourmost were a 1960s Liverpool beat group associated with the Merseybeat scene, known for their close ties to The Beatles and hits like "A Little Loving."
-
D.
Heed
Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
-
E.
Sirens
"Sirens" is a British comedy-drama television series in which Richard Madden stars as a paramedic navigating the darkly humorous and chaotic realities of emergency medical work.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64831c58819098758ac1f7839b3a |
completed | March 20, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be10b49b90819091c3ab38e976baeb |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:19 p.m.