Triple
T2226950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton, Dorset, England |
E48672
|
entity |
| Predicate | hasOriginalNameFor |
P3325
|
FINISHED |
| Object | Milton, Massachusetts town name |
—
|
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: Milton, Massachusetts town name | Statement: [Milton, Dorset, England, hasOriginalNameFor, Milton, Massachusetts town name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalNameFor Context triple: [Milton, Dorset, England, hasOriginalNameFor, Milton, Massachusetts town name]
-
A.
isOriginalFamilyNameOf
Indicates that a given family name is the original or birth surname of a person, from which any later or changed surnames may have derived.
-
B.
hasNameOrigin
chosen
Indicates that the origin or source of an entity’s name is specified by the related entity.
-
C.
originalNameLanguage
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
D.
nameInOriginalLanguage
Indicates that an entity’s name is given in its original or native language form.
-
E.
hasOriginalsBrand
Indicates that one entity is associated with, or belongs to, the Originals brand of another entity.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0411e388190b35e82ad6688bfe3 |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.