Triple
T1600231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howe |
E34373
|
entity |
| Predicate | etymologyRelatesTo |
P30589
|
FINISHED |
| Object | topographic 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: topographic name | Statement: [Howe, etymologyRelatesTo, topographic name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologyRelatesTo Context triple: [Howe, etymologyRelatesTo, topographic name]
-
A.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
B.
etymologyStatus
Indicates the status or reliability classification of an etymological explanation for a term or name.
-
C.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
-
D.
etymologyPossibleMeaning
Indicates a possible or hypothesized meaning that an etymological analysis suggests for a word or term.
-
E.
etymologicalLanguage
Indicates the language from which a word or term is historically derived in its etymology.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a95b02cd448190be8e3db9a5a7bac0 |
completed | March 5, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69a907c1cad08190b9728dd557f39aa0 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a95aada3f881909053363c01de8b57 |
completed | March 5, 2026, 10:29 a.m. |
Created at: March 4, 2026, 7:28 p.m.