Triple
T19846924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Paola |
E476886
|
entity |
| Predicate | hasSecondElementMeaningAssociation |
P137564
|
FINISHED |
| Object | small |
—
|
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: small | Statement: [Maria Paola, hasSecondElementMeaningAssociation, small]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondElementMeaningAssociation Context triple: [Maria Paola, hasSecondElementMeaningAssociation, small]
-
A.
hasSecond
Indicates that one entity is the second item, position, or element in an ordered sequence or pair relative to another entity.
-
B.
hasSecondary
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
C.
hasSecondarySubject
Indicates that an entity is associated with an additional, non-primary subject in a given context or relationship.
-
D.
hasSecondarySource
Indicates that an entity is supported, documented, or referenced by a secondary source rather than by a primary or original source.
-
E.
hasSecondaryBase
Indicates that an entity possesses or is associated with a secondary or additional base, distinct from its primary base.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65809da2c8190bb579ef42513b74d |
completed | April 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e537e21d2881909b1be82f02b99d40 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:51 p.m.