Triple
T8414224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pkgsrc |
E198693
|
entity |
| Predicate | operatingSystem |
P1593
|
FINISHED |
| Object | Haiku |
E209551
|
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: Haiku | Statement: [pkgsrc, operatingSystem, Haiku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haiku Context triple: [pkgsrc, operatingSystem, Haiku]
-
A.
Haiku
chosen
Haiku is an open-source, lightweight desktop operating system inspired by BeOS, designed for speed, simplicity, and consistency.
-
B.
tanka
The tanka was a medieval silver coin that served as a standard monetary unit across much of the Indian subcontinent under various Islamic and later dynasties.
-
C.
Temwaiku
Temwaiku is a village and district within South Tarawa in Kiribati, known as one of the populated islets forming the country's capital area.
-
D.
Haikasoru
Haikasoru is a publishing imprint of Viz Media that specializes in translating and releasing Japanese science fiction and fantasy novels in English.
-
E.
Kawi
Kawi is an ancient Brahmic script historically used in maritime Southeast Asia, particularly for Old Javanese and related languages.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e328cc8190b3b038005d0bb66f |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce032a25ec819094c6346eb2a7f973 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:06 p.m.