Triple
T18630924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucas tree model |
E455412
|
entity |
| Predicate | hasGoodType |
P132465
|
FINISHED |
| Object | single consumption good |
—
|
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: single consumption good | Statement: [Lucas tree model, hasGoodType, single consumption good]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGoodType Context triple: [Lucas tree model, hasGoodType, single consumption good]
-
A.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
B.
hasStandardType
Indicates that something conforms to or is categorized under a defined standard classification or type.
-
C.
hasFaithfulType
Indicates that one entity has a corresponding type or classification that remains consistent, reliable, or invariant with respect to some underlying structure or mapping.
-
D.
hasKeyType
Indicates that an entity possesses or is associated with a specific category or type of key.
-
E.
hasTypeName
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54f07fa8481908b2535b8fba70b7e |
completed | April 19, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69e478d4a7948190a4bb9223bb5dddfc |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e485f5d1588190b44f31cbc54c0a9d |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 11:46 a.m.