Triple
T6340795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sant Anna |
E142617
|
entity |
| Predicate | hasSpaceBetweenWords |
P36966
|
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: [Sant Anna, hasSpaceBetweenWords, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpaceBetweenWords Context triple: [Sant Anna, hasSpaceBetweenWords, true]
-
A.
isWrittenWithSpace
chosen
Indicates that something is written or represented with spaces separating its components or elements.
-
B.
hasAdditionalLetters
Indicates that one entity contains extra or more letters than another entity, beyond a specified base set or reference.
-
C.
hasHyphenation
Indicates that one entity specifies or provides the hyphenated form or hyphenation pattern of another entity.
-
D.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
E.
hasBasicWordOrder
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0674311388190bb069a07a7ff60ef |
completed | March 22, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:30 p.m.