Triple
T12417534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acer |
E296674
|
entity |
| Predicate | sapUsedFor |
P98
|
FINISHED |
| Object | maple syrup |
—
|
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: maple syrup | Statement: [Acer, sapUsedFor, maple syrup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sapUsedFor Context triple: [Acer, sapUsedFor, maple syrup]
-
A.
sapUse
Indicates that one entity uses or applies sap (such as plant resin or a sap-based substance) in relation to another entity.
-
B.
sap
Indicates the act of gradually weakening, draining, or undermining the strength, energy, or effectiveness of someone or something.
-
C.
sapType
Indicates the specific category or classification of SAP-related type assigned to an entity within a system or data model.
-
D.
sapContains
Indicates that one entity spatially or logically contains another as a part, component, or subset within its bounds.
-
E.
usedFor
chosen
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.