Triple
T17569508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babel |
E427897
|
entity |
| Predicate | usedWith |
P4791
|
FINISHED |
| Object | Grunt |
—
|
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: Grunt | Statement: [Babel, usedWith, Grunt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grunt Context triple: [Babel, usedWith, Grunt]
-
A.
Grunt
chosen
Grunt is a JavaScript-based task runner commonly used in web development to automate repetitive tasks such as building, testing, and deploying code.
-
B.
The Grunt
"The Grunt" is a 1969 funk instrumental by The J.B.'s, best known for its distinctive saxophone riff that became one of hip-hop’s most sampled breaks.
-
C.
Gulp
Gulp is a powerful, hulking dinosaur-like boss character from the Spyro the Dragon video game series, known for serving as one of Ripto’s main enforcers.
-
D.
Gulp
Gulp is a JavaScript-based task runner and build system commonly used to automate front-end development workflows such as compiling, bundling, and optimizing assets.
-
E.
The Grinder
The Grinder is an American television sitcom that satirizes legal dramas, starring Rob Lowe and Fred Savage as brothers whose lives are upended when a TV lawyer returns home believing he can practice real law.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4592fe8408190bd8fed1920ab3601 |
completed | April 19, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.