Triple
T152103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People |
E3453
|
entity |
| Predicate | formerOwner |
P347
|
FINISHED |
| Object | Meredith Corporation |
E3456
|
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: Meredith Corporation | Statement: [People, formerOwner, Meredith Corporation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meredith Corporation Context triple: [People, formerOwner, Meredith Corporation]
-
A.
Meredith Corporation
chosen
Meredith Corporation was a major American media and marketing company best known for its portfolio of lifestyle magazines and television broadcasting assets.
-
B.
Cox Enterprises
Cox Enterprises is a major U.S. privately held media, communications, and automotive services conglomerate.
-
C.
Johnson & Johnson
Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
-
D.
Groupe ADP
Groupe ADP is a major French airport management company that owns and operates the Paris-area airports and provides aviation and related services worldwide.
-
E.
Pella Corporation
Pella Corporation is a major American manufacturer of windows and doors known for its innovative, energy-efficient building products.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580f55a88190b37b54ee0ed5ac7c |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2d0c4cae881909e954f12d5bb9672 |
completed | Feb. 28, 2026, 11:25 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.