Triple
T22110163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIP |
E546390
|
entity |
| Predicate | containsRareCharacters |
P2271
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [SIP, containsRareCharacters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRareCharacters Context triple: [SIP, containsRareCharacters, true]
-
A.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
B.
hasSpecialCharacter
chosen
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
C.
hasEccentricCharacters
Indicates that something features characters who behave in unconventional, odd, or quirky ways.
-
D.
usesColloquialCharacters
Indicates that an expression, name, or text is written using informal, non-standard, or colloquial characters rather than formal or standard script.
-
E.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
- F. None of above.
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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12948c2ec819083340787b2062649 |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:30 p.m.