Triple
T14818832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommo |
E348388
|
entity |
| Predicate | hasAlternativeCapitalization |
P457
|
FINISHED |
| Object | tommo |
—
|
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: tommo | Statement: [Tommo, hasAlternativeCapitalization, tommo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeCapitalization Context triple: [Tommo, hasAlternativeCapitalization, tommo]
-
A.
hasAlternativeVocalization
Indicates that an entity has another valid way it can be vocalized or pronounced, distinct from its primary or standard vocalization.
-
B.
preferredCapitalization
Indicates the specific way a term’s letters should be capitalized when it is written or displayed.
-
C.
hasAlternativeNotation
Indicates that an entity can be represented or written in a different, equivalent form or notation.
-
D.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
E.
hasDistinctLetterForms
Indicates that the related writing system or symbol set uses different visual shapes or styles for the same letter in different contexts (such as position, case, or usage).
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe4cf38819090f25ef045351d5d |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:50 a.m.