Triple
T12455253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Milla |
E297639
|
entity |
| Predicate | ageRecord |
P105092
|
FINISHED |
| Object | oldest goal scorer in FIFA World Cup history at the time |
—
|
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: oldest goal scorer in FIFA World Cup history at the time | Statement: [Roger Milla, ageRecord, oldest goal scorer in FIFA World Cup history at the time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageRecord Context triple: [Roger Milla, ageRecord, oldest goal scorer in FIFA World Cup history at the time]
-
A.
ageDetail
Indicates a detailed specification of an entity’s age, such as exact value, range, or related age attributes.
-
B.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
-
C.
ageModel
Indicates a relationship where one entity specifies or provides the age of another entity, typically in terms of a particular age value or age-related classification.
-
D.
ageBased
Indicates a relationship or condition that depends on or is determined by the age of the entities involved.
-
E.
ageProgression
Indicates a temporal relationship where an entity’s age increases or advances over time.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d9511989ac8190ade98f52f66f7cd4 |
completed | April 10, 2026, 7:35 p.m. |
Created at: April 8, 2026, 9:56 p.m.