Triple
T25101956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcel Weber |
E628750
|
entity |
| Predicate | nameAmbiguity |
P92520
|
FINISHED |
| Object | refers to multiple individuals |
—
|
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: refers to multiple individuals | Statement: [Marcel Weber, nameAmbiguity, refers to multiple individuals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameAmbiguity Context triple: [Marcel Weber, nameAmbiguity, refers to multiple individuals]
-
A.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
B.
namedForConflict
Indicates that one entity is named after, or in commemoration of, a specific conflict, war, or battle.
-
C.
nameContrastsWith
Indicates that one name is deliberately chosen or used to highlight a difference or opposition in meaning, style, or identity relative to another name.
-
D.
nameMayReferTo
chosen
Indicates that a given name or label can ambiguously denote or be used for one or more possible entities.
-
E.
nameDistinction
Indicates that two entities are distinguished from one another specifically by differences in their names.
- 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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f464be45448190b42c7d880d8550c8 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:25 a.m.