Triple
T19704337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meg Hourihan |
E473172
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Meg |
—
|
NE NERFINISHED |
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: Meg | Statement: [Meg Hourihan, givenName, Meg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meg Context triple: [Meg Hourihan, givenName, Meg]
-
A.
Meg
chosen
Meg is a common diminutive form of the female given name Margaret, often used in English-speaking countries.
-
B.
Megan
Megan is a fictional character from the television series "Lucifer," portrayed by actress Scarlett Estevez.
-
C.
Megan
Megan is a feminine given name of Greek origin, commonly used in English-speaking countries as a variant of Margaret.
-
D.
Megan
Megan is the stepmother of Brad Whitaker.
-
E.
Megan
Megan is a central fictional character in the Australian television drama series "The Newsreader," which explores the personal and professional lives of 1980s newsroom staff.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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. |
Created at: April 10, 2026, 1:46 p.m.