Triple
T1883203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-Louise |
E39898
|
entity |
| Predicate | commonInOnomastics |
P34347
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Marie-Louise, commonInOnomastics, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonInOnomastics Context triple: [Marie-Louise, commonInOnomastics, yes]
-
A.
hasOnomasticField
Indicates a relationship where something is associated with a specific onomastic field, i.e., a domain or category related to names or naming conventions.
-
B.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
-
C.
sharesEtymologyWith
Indicates that two terms originate from the same linguistic root or source word, or have closely related historical word origins.
-
D.
nameGivesRiseTo
Indicates that one name, term, or designation leads to, causes, or results in the emergence or establishment of another.
-
E.
etymologyRelatesTo
Indicates a relationship where one term’s origin, history, or derivation is connected to another linguistic form, word, or source.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb4f53f408190ae30e1a12721e7d7 |
completed | March 7, 2026, 5:17 a.m. |
| PD | Predicate disambiguation | batch_69abafe497a88190a1da6af2888b71b4 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb4f3fb9481908b54506dc2836124 |
completed | March 7, 2026, 5:17 a.m. |
Created at: March 4, 2026, 7:34 p.m.