Triple
T20472886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borgin and Burkes |
E502236
|
entity |
| Predicate | timePeriodOfEmployment_TomRiddle |
P75989
|
FINISHED |
| Object | after Hogwarts graduation |
—
|
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: after Hogwarts graduation | Statement: [Borgin and Burkes, timePeriodOfEmployment_TomRiddle, after Hogwarts graduation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfEmployment_TomRiddle Context triple: [Borgin and Burkes, timePeriodOfEmployment_TomRiddle, after Hogwarts graduation]
-
A.
occupationDuration
Indicates the length of time an entity holds or has held a particular occupation or role.
-
B.
timePeriodOfWorks
Indicates the span of time during which the associated works were created, produced, or active.
-
C.
timeInOfficeCharacteristic
Indicates a characteristic or attribute specifically related to the duration or period an entity spends in office or in a particular official role.
-
D.
hasTimePeriodOfService
chosen
Indicates that an entity is associated with a specific span of time during which it provided service or was actively serving.
-
E.
teamTenure
Indicates the duration or length of time an entity has been part of a particular team.
- F. None of above.
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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69962d810819091bb13fe73250e24 |
completed | April 20, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.