Triple
T32894576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | little Mary |
E841432
|
entity |
| Predicate | canBeAddressFormFor |
P4477
|
FINISHED |
| Object | a child |
—
|
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: a child | Statement: [little Mary, canBeAddressFormFor, a child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeAddressFormFor Context triple: [little Mary, canBeAddressFormFor, a child]
-
A.
canAddress
Indicates that one entity has the ability or permission to direct communication, action, or service toward another entity.
-
B.
addressFormFor
chosen
Indicates the form of address or mode of speaking that one entity should use when referring to or speaking to another entity.
-
C.
addressedFor
Indicates that something is directed, designated, or intended for a particular recipient or target.
-
D.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
E.
hasFormFor
Indicates that one entity possesses or provides a specific form or document intended to be used by another entity or for a particular purpose.
- 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe6fea4a288190bf8615c5d6bf41b4 |
completed | May 8, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69fe6f774de08190975a2393b9a1fd22 |
completed | May 8, 2026, 11:19 p.m. |
Created at: May 1, 2026, 1:18 a.m.