Triple
T6115274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga |
E136344
|
entity |
| Predicate | cognate |
P2527
|
FINISHED |
| Object | Helga |
E319163
|
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: Helga | Statement: [Olga, cognate, Helga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helga Context triple: [Olga, cognate, Helga]
-
A.
Helga
chosen
Helga is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
-
B.
Helga Gumm
Helga Gumm is a character in the "Spy Kids" film series, known as the grandmother of the Cortez children and a former spy herself.
-
C.
Baerbel
Baerbel is a feminine given name of German origin, commonly used as an alternative spelling of Bärbel.
-
D.
Gisela
Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
-
E.
Huberta
Huberta is a feminine given name of Dutch origin, used in full or as part of compound names such as Everdine Huberta van Wijnbergen.
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bc0bee08190ab93eae34ea8cdde |
completed | March 22, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1359ed8608190a99c9e5b0f384c63 |
completed | March 23, 2026, 12:44 p.m. |
Created at: March 22, 2026, 4:14 p.m.