Triple
T5894974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TJ Holowaychuk |
E131079
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | Go |
E17649
|
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: Go | Statement: [TJ Holowaychuk, programmingLanguage, Go]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Go Context triple: [TJ Holowaychuk, programmingLanguage, Go]
-
A.
Go
Go is an ancient East Asian abstract strategy board game, renowned for its simple rules yet immense strategic depth, played on a grid with black and white stones.
-
B.
Go
chosen
Go is a statically typed, compiled programming language developed at Google, known for its simplicity, efficient concurrency support, and suitability for scalable networked and cloud services.
-
C.
Go
"Go" is a surf rock song, likely characterized by upbeat rhythms and guitar-driven melodies typical of the genre.
-
D.
Go
Go is a 1999 ensemble crime-comedy film known for its interlocking stories, fast-paced narrative, and energetic depiction of a wild night involving drugs, raves, and misadventures.
-
E.
go90
go90 was a now-defunct American mobile video streaming service owned by Verizon that offered live and on-demand sports, entertainment, and original programming.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036f3364c81909353f62ca483f24f |
completed | March 22, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b1558fa48190a6ecde69c1477863 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.