Triple
T3123454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hathor |
E65238
|
entity |
| Predicate | relatedDeity |
P23286
|
FINISHED |
| Object | Bastet |
E24792
|
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: Bastet | Statement: [Hathor, relatedDeity, Bastet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bastet Context triple: [Hathor, relatedDeity, Bastet]
-
A.
Bastet
chosen
Bastet is an ancient Egyptian goddess, often depicted as a lioness or cat, associated with home, fertility, music, and the protective, nurturing aspects of the sun.
-
B.
Nekhbet
Nekhbet is an ancient Egyptian vulture goddess who served as the protective patron deity of Upper Egypt and the pharaoh.
-
C.
Wadjet
Wadjet is an ancient Egyptian cobra goddess associated with royal protection, kingship, and the land of Lower Egypt.
-
D.
Sekhmet
Sekhmet is an ancient Egyptian lioness-headed goddess associated with war, destruction, and healing, revered as a powerful protector and bringer of both plague and cure.
-
E.
Mr. Mistoffelees
Mr. Mistoffelees is a magical black-and-white cat character from T. S. Eliot’s poetry, best known today through his prominent role in the musical "Cats."
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52c105c8190b8128e66d9b9e8a0 |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f72c2048190ab2aa40a109f5976 |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.