Triple
T24825873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMM |
E621187
|
entity |
| Predicate | hasFrenchEquivalentPostNominal |
P147165
|
FINISHED |
| Object | M.M.M. |
—
|
NE NERFINISHED |
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: M.M.M. | Statement: [MMM, hasFrenchEquivalentPostNominal, M.M.M.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrenchEquivalentPostNominal Context triple: [MMM, hasFrenchEquivalentPostNominal, M.M.M.]
-
A.
equivalentFrenchPostNominal
chosen
Indicates that one entity has a corresponding or matching French post-nominal form equivalent to that of another entity.
-
B.
correspondsToAbbreviationInFrench
Indicates that one entity is the full form or expression for which the other entity serves as the abbreviation in French.
-
C.
hasPostnominalLetters
Indicates that a person holds specific postnominal letters (abbreviations after their name) signifying qualifications, honors, or titles.
-
D.
nameInFrench
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
E.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
- 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_69e2fac0c3b881909110e5a56c6fa46f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:05 a.m.