Triple
T8756079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YAML |
E208075
|
entity |
| Predicate | acronymFor |
P590
|
FINISHED |
| Object | YAML Ain't Markup Language |
E208075
|
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: YAML Ain't Markup Language | Statement: [YAML, acronymFor, YAML Ain't Markup Language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: YAML Ain't Markup Language Context triple: [YAML, acronymFor, YAML Ain't Markup Language]
-
A.
YAML
chosen
YAML is a human-readable data serialization language commonly used for configuration files and data exchange, emphasizing simplicity and ease of editing.
-
B.
Yet Another Markup Language
Yet Another Markup Language is a human-readable data serialization format commonly used for configuration files and data exchange in programming and DevOps environments.
-
C.
YAM
YAM is the IATA airport code for Sault Ste. Marie Airport in Ontario, Canada.
-
D.
TOML
TOML is a human-readable configuration file format designed for simplicity and unambiguous parsing, commonly used in modern software tooling and package managers.
-
E.
CommonMark
CommonMark is a standardized, highly compatible specification of Markdown syntax designed to eliminate ambiguities and ensure consistent rendering across different implementations.
- 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_69ca835cd6b08190bd7c63db92f53c86 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dd95e9481909cc88e8d91601754 |
completed | March 31, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf519175248190b53c8958cfeeebfa |
completed | April 3, 2026, 5:35 a.m. |
Created at: March 30, 2026, 6:40 p.m.