Triple
T10609406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gili Landau |
E275965
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Landau |
E334540
|
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: Landau | Statement: [Gili Landau, familyName, Landau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landau Context triple: [Gili Landau, familyName, Landau]
-
A.
Landau
chosen
Landau is a surname most famously associated with Lev Landau, the Nobel Prize–winning Soviet theoretical physicist known for his groundbreaking work in quantum mechanics and condensed matter physics.
-
B.
Landau
Landau is a historic fortified town in southwestern Germany’s Rhineland-Palatinate, long valued for its strategic military position in Europe.
-
C.
Balkhausen
Balkhausen is a district within the town of Kerpen in North Rhine-Westphalia, Germany.
-
D.
Miltenberg
Miltenberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town along the Main River and its timber-framed architecture.
-
E.
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4d0a6881909fea20378085173d |
completed | April 8, 2026, 11:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95ebe539881908aeff1cd65cf925f |
completed | April 10, 2026, 8:34 p.m. |
Created at: April 8, 2026, 7:32 p.m.