Triple
T3948622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amphissus |
E84807
|
entity |
| Predicate | childOf |
P120
|
FINISHED |
| Object | Apollo |
E12942
|
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: Apollo | Statement: [Amphissus, childOf, Apollo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apollo Context triple: [Amphissus, childOf, Apollo]
-
A.
Apollo
chosen
Apollo is the Olympian god of the sun, music, prophecy, and healing in ancient Greek mythology.
-
B.
Apollo
Apollo is a small borough in Armstrong County, Pennsylvania, known historically as a riverfront industrial community along the Kiskiminetas River.
-
C.
Apollo Karneios
Apollo Karneios is a pastoral and oracular aspect of the Greek god Apollo particularly venerated in the Dorian regions of the ancient Greek world, where he was associated with flocks, seasonal cycles, and communal festivals.
-
D.
Apollo Loxias
Apollo Loxias is an epithet of the Greek god Apollo emphasizing his role as an oracular deity whose prophetic messages are often ambiguous or obscure.
-
E.
Juno
Juno is a 2007 coming-of-age comedy-drama film about a witty teenager dealing with an unplanned pregnancy, widely praised for its sharp dialogue and performances.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef910ecc08190a4fca89bcf063e0c |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5339feb4c8190ad96a5680cb5294e |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:30 p.m.