Triple
T4917637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GreekMonsters |
E110386
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object | Sphinx |
E111286
|
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: Sphinx | Statement: [GreekMonsters, includes, Sphinx]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sphinx Context triple: [GreekMonsters, includes, Sphinx]
-
A.
Sphinx
chosen
The Sphinx is a mythical creature, typically depicted with a lion's body and a human head, known for posing deadly riddles to travelers in Greek mythology.
-
B.
Sphinx
Sphinx is a documentation generation tool that converts reStructuredText (and other formats) into HTML, PDF, and other outputs, widely used for Python projects and technical documentation.
-
C.
Sphinx of Naxos
The Sphinx of Naxos is an ancient Greek monumental statue of a winged female sphinx dedicated by the island of Naxos at Delphi, renowned for its Archaic style and imposing scale.
-
D.
Thoth
Thoth is the ancient Egyptian god of writing, wisdom, magic, and the moon, often depicted as an ibis-headed scribe of the gods.
-
E.
Pythias
Pythias was the first wife of the ancient Greek philosopher Aristotle and the mother of his daughter, also named Pythias.
- 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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6fa760448190946401b4b21ea8b7 |
completed | March 20, 2026, 4:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77a1ef488190ac9cc34e67a8b243 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:29 p.m.