Triple
T10359557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-Thérèse |
E244097
|
entity |
| Predicate | writtenWithHyphen |
P64072
|
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: [Marie-Thérèse, writtenWithHyphen, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writtenWithHyphen Context triple: [Marie-Thérèse, writtenWithHyphen, true]
-
A.
isWrittenWithApostrophe
Indicates that something (typically a word, phrase, or name) is written using an apostrophe character as part of its spelling or punctuation.
-
B.
hasHyphenation
chosen
Indicates that one entity specifies or provides the hyphenated form or hyphenation pattern of another entity.
-
C.
isWrittenWithSpace
Indicates that something is written or represented with spaces separating its components or elements.
-
D.
writtenWithCharacter
Indicates that something is written using a particular character or set of characters as its writing system or notation.
-
E.
writtenIn
Indicates that a work (such as a text, program, or document) is expressed or encoded using a particular language or notation.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9609c4481908b7d72ecf1adaa73 |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:59 a.m.