Triple
T934137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heracles |
E20157
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Hebe |
E107396
|
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: Hebe | Statement: [Heracles, spouse, Hebe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hebe Context triple: [Heracles, spouse, Hebe]
-
A.
Hebe
chosen
Hebe is the Greek goddess of youth, traditionally known as the cupbearer of the gods on Mount Olympus.
-
B.
Maia
Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
-
C.
Sonia
Sonia is a central female character in the romantic comedy film "Think Like a Man," whose relationships and personal growth intersect with the movie’s ensemble cast and themes about modern dating.
-
D.
Diana
Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
-
E.
Luisa
Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3627ccc8190a836515b2ea85ec5 |
completed | March 1, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1cd3444881908615a7962b4eef67 |
completed | March 7, 2026, 12:40 p.m. |
Created at: March 1, 2026, 7:40 p.m.