Triple
T23999119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epstein (Eppstein), Hesse, Germany |
E594192
|
entity |
| Predicate | hasHistoricalSpelling |
P66486
|
FINISHED |
| Object | Epstein |
—
|
NE NERFINISHED |
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: Epstein | Statement: [Epstein (Eppstein), Hesse, Germany, hasHistoricalSpelling, Epstein]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalSpelling Context triple: [Epstein (Eppstein), Hesse, Germany, hasHistoricalSpelling, Epstein]
-
A.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
B.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
C.
hasHistoricNameVariant
chosen
Indicates that an entity has an alternative name that was used in a historical period or past context.
-
D.
historicallySpoke
Indicates that an entity used a particular language as a spoken language during some period in the past.
-
E.
historicalLanguageFeature
Indicates that a language possesses a feature, trait, or characteristic that existed or was relevant in a past historical period.
- 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_69e288b9ecf08190b8c94a278f5674fe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d460b07881908ad11c03890ec1de |
completed | April 29, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:39 p.m.