Triple
T18015366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Read the Docs |
E430985
|
entity |
| Predicate | uses |
P98
|
FINISHED |
| Object | Sphinx |
—
|
NE NERFINISHED |
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: [Read the Docs, uses, Sphinx]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sphinx Context triple: [Read the Docs, uses, Sphinx]
-
A.
Sphinx
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
chosen
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
Sphinx is a taciturn, highly skilled mechanic and member of the car-stealing crew in the film "Gone in 60 Seconds."
-
D.
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.
-
E.
The Sphinx
The Sphinx is the official magazine of Alpha Phi Alpha Fraternity, Inc., serving as a historical record and communication organ for its members.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b522e84c8190a03f6445df9f5ac8 |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.