Triple
T4220014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bee Gees |
E94315
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Words |
E417120
|
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: Words | Statement: [Bee Gees, notableWork, Words]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Words Context triple: [Bee Gees, notableWork, Words]
-
A.
Words
chosen
"Words" is a popular song by the Bee Gees, notable for its gentle melody and heartfelt lyrics that have made it a classic ballad.
-
B.
Writing and Language
Writing and Language is a PSAT/NMSQT subsection that tests students’ ability to revise and edit passages for clarity, grammar, usage, and effective written expression.
-
C.
Lang
Lang is the given name of the renowned Chinese concert pianist Lang Lang, celebrated for his virtuosic technique and charismatic performances.
-
D.
Of Words
"Of Words" is a chapter in Book III that examines the nature, use, and significance of language and terminology.
-
E.
The Words
The Words is Jean-Paul Sartre’s autobiographical work in which he reflects on his childhood and the development of his literary and philosophical identity.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e0c84548190b051d32d434cbf04 |
completed | March 12, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5963ffacc8190843b60ea1b224f91 |
completed | March 14, 2026, 5:09 p.m. |
Created at: March 12, 2026, 11:04 p.m.