Triple
T26896262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Robber Girl |
E677905
|
entity |
| Predicate | relationshipToGerda |
P198690
|
FINISHED |
| Object | helper |
—
|
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: helper | Statement: [Little Robber Girl, relationshipToGerda, helper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToGerda Context triple: [Little Robber Girl, relationshipToGerda, helper]
-
A.
relationshipToGerdaWegener
Indicates the specific type of personal or social relationship an entity has with Gerda Wegener.
-
B.
relationshipToGertrude
Indicates the specific type of personal, familial, or social relationship that one entity has to Gertrude.
-
C.
relationshipToEva
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
D.
relationshipToJohanna
Indicates the specific type of relationship or connection that an entity has with Johanna.
-
E.
relationshipToMary
Indicates that one entity stands in a specified personal or social relationship to Mary.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
| PDg | Predicate description generation | batch_69feff703fec8190ab7d0633e0cc5459 |
completed | May 9, 2026, 9:33 a.m. |
Created at: April 27, 2026, 5:48 a.m.