Triple
T20535169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpha Phi Alpha |
E504174
|
entity |
| Predicate | symbol |
P129
|
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: [Alpha Phi Alpha, symbol, sphinx]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: sphinx Context triple: [Alpha Phi Alpha, symbol, sphinx]
-
A.
Sphinx documentation
Sphinx documentation is the official and user-generated reference material that explains how to use the Sphinx tool to create, configure, and build structured software documentation.
-
B.
Sphinx AT 2000
The Sphinx AT 2000 is a high-quality Swiss-made semi-automatic pistol renowned for its precision engineering, reliability, and refined ergonomics.
-
C.
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.
-
D.
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.
-
E.
Sphinx
Sphinx is a taciturn, highly skilled mechanic and member of the car-stealing crew in the film "Gone in 60 Seconds."
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06df04081908fa95c6214f06093 |
completed | April 20, 2026, 9:53 p.m. |
Created at: April 16, 2026, 11:37 a.m.