Triple
T372442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Zuckerberg |
E8295
|
entity |
| Predicate | hasWrittenFor |
P11775
|
FINISHED |
| Object | popular and academic outlets on classics and politics |
—
|
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: popular and academic outlets on classics and politics | Statement: [Donna Zuckerberg, hasWrittenFor, popular and academic outlets on classics and politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWrittenFor Context triple: [Donna Zuckerberg, hasWrittenFor, popular and academic outlets on classics and politics]
-
A.
areWrittenOn
Indicates that one entity serves as a surface or medium on which another entity is inscribed, recorded, or written.
-
B.
usedToWrite
Indicates that one entity served as a tool, medium, or instrument that another entity employed to perform the act of writing.
-
C.
wrote
Indicates that an entity is the author or creator of a written work involving another entity.
-
D.
hasAuthor
Indicates that an entity is written or created by a specific author.
-
E.
writtenDuring
Indicates that the creation or authorship of something took place within a specified time period or historical event.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec018d508190b5687a9ba90b3092 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e960d880819084b3df4e5137a1e2 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0b23ec8190bef9d593162388a4 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.