Triple
T36624250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mâcon-Villages |
E904126
|
entity |
| Predicate | canBeLabeledAs |
P180495
|
FINISHED |
| Object |
Mâcon-Villages
Mâcon-Villages is a French appellation in southern Burgundy known for producing fresh, fruit-driven white wines primarily from Chardonnay grapes.
|
E2193182
|
NE FINISHED |
How this triple was built (3 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: Mâcon-Villages | Statement: [Mâcon-Villages, canBeLabeledAs, Mâcon-Villages]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mâcon-Villages Triple: [Mâcon-Villages, canBeLabeledAs, Mâcon-Villages]
Generated description
Mâcon-Villages is a French appellation in southern Burgundy known for producing fresh, fruit-driven white wines primarily from Chardonnay grapes.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeLabeledAs Context triple: [Mâcon-Villages, canBeLabeledAs, Mâcon-Villages]
-
A.
isLabeledOn
Indicates that a label, tag, or identifying text is physically or virtually attached to or displayed on an entity.
-
B.
canBeNamed
chosen
Indicates that an entity is capable of being assigned or given a specific name or label.
-
C.
hasLabel
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
-
D.
canBeDesignatedAs
Indicates that one entity is eligible or suitable to be formally assigned, labeled, or recognized under a particular role, status, or designation.
-
E.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
- F. None of above.
Provenance (6 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69feecf1bb248190ba30f0bb1d22ee08 |
completed | May 9, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3a09644d5c819088de7ad42a764fe4 |
completed | June 23, 2026, 4:19 a.m. |
| NEDg | Description generation | batch_6a3a0cec02d48190b4770d012b5208a4 |
completed | June 23, 2026, 4:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3a179310d08190a89d4feaf3e4c6e0 |
completed | June 23, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69feea5f27748190b223ee4e3ba5a678 |
completed | May 9, 2026, 8:03 a.m. |
Created at: May 3, 2026, 4:11 p.m.