Triple
T34954476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNU All-permissive License |
E1008090
|
entity |
| Predicate | hasTextLength |
P196399
|
FINISHED |
| Object | very short |
—
|
LITERAL 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: very short | Statement: [GNU All-permissive License, hasTextLength, very short]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextLength Context triple: [GNU All-permissive License, hasTextLength, very short]
-
A.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
B.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
C.
hasMaximumLength
Indicates that there is an upper limit on the length or size of something, beyond which it cannot extend.
-
D.
hasMinimumLength
Indicates that the length of an entity (such as a sequence, string, or collection) is greater than or equal to a specified minimum value.
-
E.
hasLengthRange
Indicates that an entity’s length falls within a specified minimum-to-maximum range.
- F. None of above. chosen
Provenance (4 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69fe30bb07d08190877539d5aa202d24 |
completed | May 8, 2026, 6:51 p.m. |
Created at: May 3, 2026, 4 p.m.