Triple
T35808162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boss |
E1035156
|
entity |
| Predicate | hasRealNameOfUser |
P9233
|
FINISHED |
| Object | Mercedes Justine Kaestner-Varnado |
E1035153
|
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: Mercedes Justine Kaestner-Varnado | Statement: [The Boss, hasRealNameOfUser, Mercedes Justine Kaestner-Varnado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRealNameOfUser Context triple: [The Boss, hasRealNameOfUser, Mercedes Justine Kaestner-Varnado]
-
A.
realName
chosen
Indicates that one entity is the actual, full, or birth name of another entity, which may be known by an alias, nickname, or alternate identity.
-
B.
usedByRealName
Indicates that something (such as an alias, handle, or resource) is used by an entity identified by their real, legal name.
-
C.
notRealNameOf
Indicates that the referenced name is not the entity’s actual or official name (e.g., it is false, fabricated, or otherwise not the real name of that entity).
-
D.
hasGivenNameOfRealPerson
Indicates that an entity bears the same given (first) name as a specific real person.
-
E.
hasAuthorRealName
Indicates that an entity (such as a work or pseudonym) is associated with the actual, legal name of its author.
- F. None of above.
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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38b6e7b3208190ac8528e2e37c6a7a |
completed | June 22, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.