Triple
T1321660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loretta Young |
E28231
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gretchen |
E98327
|
NE 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: Gretchen | Statement: [Loretta Young, givenName, Gretchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gretchen Context triple: [Loretta Young, givenName, Gretchen]
-
A.
Gretchen
Gretchen is the given name of Gretchen C. Daily, an influential American ecologist and environmental scientist known for her work on biodiversity conservation and ecosystem services.
-
B.
Gretchen
chosen
Gretchen is a feminine given name, traditionally used in German-speaking regions and often recognized as a diminutive form of Margaret.
-
C.
Bettina
Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
-
D.
Dorothee
Dorothee is a feminine given name, commonly used in German- and French-speaking countries, that is a variant of the name Dorothea.
-
E.
Heike Makatsch
Heike Makatsch is a German actress and former television presenter known internationally for her roles in films such as "Love Actually" and "Resident Evil."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19932888190a3d45871e84f112e |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbaf6a6d08190b8a30c2c64f15f59 |
completed | March 7, 2026, 11:55 p.m. |
Created at: March 1, 2026, 7:55 p.m.