Triple
T34640190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvan tongue |
E889533
|
entity |
| Predicate | hasCanonicalData |
P200131
|
FINISHED |
| Object | very limited vocabulary attested |
—
|
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: very limited vocabulary attested | Statement: [Silvan tongue, hasCanonicalData, very limited vocabulary attested]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalData Context triple: [Silvan tongue, hasCanonicalData, very limited vocabulary attested]
-
A.
hasCanonicalRepresentation
Indicates that one entity is the standard or authoritative form in which another entity is represented.
-
B.
hasCanonicalReference
Indicates that one entity serves as the authoritative or standard reference source for another entity.
-
C.
hasCanonicalStructure
Indicates that an entity conforms to or is associated with a standard, officially recognized structural form.
-
D.
hasCanonicalContext
Indicates that something is associated with its primary, standard, or officially recognized contextual setting or framework.
-
E.
hasCanonicalLength
Indicates that something possesses a standard or officially defined length used as a reference or norm.
- 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_69f349d724848190b63ad3407e0006d9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
| PDg | Predicate description generation | batch_69ff76ab9b4c8190b4cc7c9c733b2765 |
completed | May 9, 2026, 6:02 p.m. |
Created at: May 1, 2026, 2:04 a.m.