Triple
T32341550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Hollis |
E826329
|
entity |
| Predicate | relationshipToAnthonyFremont |
P206253
|
FINISHED |
| Object | adult resident under Anthony's control |
—
|
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: adult resident under Anthony's control | Statement: [Dan Hollis, relationshipToAnthonyFremont, adult resident under Anthony's control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAnthonyFremont Context triple: [Dan Hollis, relationshipToAnthonyFremont, adult resident under Anthony's control]
-
A.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
B.
relationshipToBrunoAntony
Indicates a relationship that an entity has with Bruno Antony, specifying how it is connected or related to him.
-
C.
relationshipToFrancis
Indicates the specific familial, social, or professional connection that an entity has with Francis.
-
D.
relationshipToTracyLord
Indicates the specific type of personal or social relationship an entity has with Tracy Lord.
-
E.
relationshipToArmandAubigny
Indicates the specific nature of the relationship an entity has with Armand Aubigny.
- 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:48 a.m.