Triple
T25352040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madeleine McCann disappearance |
E635712
|
entity |
| Predicate | hasSuspect |
P166117
|
FINISHED |
| Object | Christian Brückner |
—
|
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: Christian Brückner | Statement: [Madeleine McCann disappearance, hasSuspect, Christian Brückner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuspect Context triple: [Madeleine McCann disappearance, hasSuspect, Christian Brückner]
-
A.
isSuspiciousOf
Indicates that one entity believes another entity or situation may be untrustworthy, harmful, or involved in wrongdoing.
-
B.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
C.
hasSuspension
Indicates that one entity is subject to a temporary suspension imposed or recorded by another entity.
-
D.
hasPotential
Indicates that an entity possesses the capacity or possibility to develop, achieve, or exhibit a particular state, quality, or outcome in the future.
-
E.
hasSucker
Indicates that one entity possesses or is equipped with a sucker used for attachment, adhesion, or suction in relation to another entity.
- 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_69e75a9ac5d881909387ed766e20cd47 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f66003a3f48190a2ba6da5aafbb5cb |
completed | May 2, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65f75ac608190a62cd6afce14f68e |
completed | May 2, 2026, 8:32 p.m. |
Created at: April 21, 2026, 1:34 p.m.