Triple
T20773720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peugeot 403 convertible |
E511301
|
entity |
| Predicate | statusInColumbo |
P141463
|
FINISHED |
| Object | signature car of Columbo |
—
|
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: signature car of Columbo | Statement: [Peugeot 403 convertible, statusInColumbo, signature car of Columbo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusInColumbo Context triple: [Peugeot 403 convertible, statusInColumbo, signature car of Columbo]
-
A.
lawEnforcementStatus
Indicates the relationship between an entity and its current standing or condition with respect to law enforcement, such as being under investigation, wanted, detained, or cleared.
-
B.
statusInSira
Indicates the status or standing that an entity holds within the Sira system or classification.
-
C.
statusInMedina
Indicates the status, role, or standing that an entity holds specifically within the context of Medina.
-
D.
statusInSI
Indicates that an entity’s status or condition is specified according to the International System of Units (SI) or an SI-based standard.
-
E.
statusInChile
Indicates the legal, social, or operational status that an entity holds specifically within the context of Chile.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c269638881909d96b847f7de5585 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3cbe5788190b7ace43bfdac2ef6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:37 p.m.