Triple
T19704358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meg Hourihan |
E473172
|
entity |
| Predicate | hasBlog |
P80
|
FINISHED |
| Object |
megnut.com
megnut.com is the personal blog of writer and technologist Meg Hourihan, known for her early influence in the blogging community.
|
E1391295
|
NE FINISHED |
How this triple was built (4 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: megnut.com | Statement: [Meg Hourihan, hasBlog, megnut.com]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: megnut.com Context triple: [Meg Hourihan, hasBlog, megnut.com]
-
A.
MNT
MNT is the Mongolian tögrög, the official national currency of Mongolia.
-
B.
Mint
Mint is an Indian business and financial daily newspaper known for its in-depth coverage of markets, economy, and corporate affairs.
-
C.
Mint
Mint is a popular personal finance management service and app that helps users track spending, budgets, and financial accounts in one place.
-
D.
Nutt
Nutt is a surname most notably associated with David Nutt, a British neuropsychopharmacologist known for his research on the effects of drugs on the brain and for advising on drug policy.
-
E.
NUTN
NUTN is the abbreviation for the National University of Tainan, a public university in Tainan, Taiwan known for its teacher education and humanities programs.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: megnut.com Triple: [Meg Hourihan, hasBlog, megnut.com]
Generated description
megnut.com is the personal blog of writer and technologist Meg Hourihan, known for her early influence in the blogging community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: megnut.com Target entity description: megnut.com is the personal blog of writer and technologist Meg Hourihan, known for her early influence in the blogging community.
-
A.
MNT
MNT is the Mongolian tögrög, the official national currency of Mongolia.
-
B.
Mint
Mint is an Indian business and financial daily newspaper known for its in-depth coverage of markets, economy, and corporate affairs.
-
C.
Mint
Mint is a popular personal finance management service and app that helps users track spending, budgets, and financial accounts in one place.
-
D.
Nutt
Nutt is a surname most notably associated with David Nutt, a British neuropsychopharmacologist known for his research on the effects of drugs on the brain and for advising on drug policy.
-
E.
NUTN
NUTN is the abbreviation for the National University of Tainan, a public university in Tainan, Taiwan known for its teacher education and humanities programs.
- F. None of above. chosen
Provenance (5 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642b998608190a82f23bbf77f7bd2 |
completed | April 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ab98bda48190b61ac274459954bd |
completed | May 15, 2026, 11:26 p.m. |
| NEDg | Description generation | batch_6a07acc9e5488190ba55f47af118fca2 |
completed | May 15, 2026, 11:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ad8aefc4819098768025121123ba |
completed | May 15, 2026, 11:34 p.m. |
Created at: April 10, 2026, 1:46 p.m.