Triple
T13814923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heartland |
E331987
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Michelle Morgan
Michelle Morgan is a Canadian actress best known for playing Lou Fleming on the long-running family drama series "Heartland."
|
E1192702
|
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: Michelle Morgan | Statement: [Heartland, portrayedBy, Michelle Morgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Morgan Context triple: [Heartland, portrayedBy, Michelle Morgan]
-
A.
Michelle Moran
Michelle Moran is the wife of American actor and producer Michael Chiklis.
-
B.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
-
C.
Tanya Morgan
Tanya Morgan is an American hip hop group known for their witty, soulful, and concept-driven rap music emerging from the mid-2000s underground scene.
-
D.
Georgia Morgan
Georgia Morgan is the founder of The International Cat Association, a major global registry and governing body for pedigreed and household pet cats.
-
E.
Jane Morgan
Jane Morgan is an American traditional pop singer who gained popularity in the 1950s and 1960s with a series of hit recordings in both the United States and Europe.
- 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: Michelle Morgan Triple: [Heartland, portrayedBy, Michelle Morgan]
Generated description
Michelle Morgan is a Canadian actress best known for playing Lou Fleming on the long-running family drama series "Heartland."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Morgan Target entity description: Michelle Morgan is a Canadian actress best known for playing Lou Fleming on the long-running family drama series "Heartland."
-
A.
Michelle Moran
Michelle Moran is the wife of American actor and producer Michael Chiklis.
-
B.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
-
C.
Tanya Morgan
Tanya Morgan is an American hip hop group known for their witty, soulful, and concept-driven rap music emerging from the mid-2000s underground scene.
-
D.
Georgia Morgan
Georgia Morgan is the founder of The International Cat Association, a major global registry and governing body for pedigreed and household pet cats.
-
E.
Jane Morgan
Jane Morgan is an American traditional pop singer who gained popularity in the 1950s and 1960s with a series of hit recordings in both the United States and Europe.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe46175b88190ae687073ddaa3d22 |
completed | May 10, 2026, 1:50 a.m. |
| NEDg | Description generation | batch_69ffe63f757c81908c7dc3c5ae3075c6 |
completed | May 10, 2026, 1:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffe6b3f25481908dd4b6108b5d95c0 |
completed | May 10, 2026, 2 a.m. |
Created at: April 9, 2026, 10:12 p.m.