Triple
T13694737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proud Mary |
E328354
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Christian Swegal
Christian Swegal is a writer best known for his work on the film "Proud Mary."
|
E1106224
|
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: Christian Swegal | Statement: [Proud Mary, writer, Christian Swegal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Swegal Context triple: [Proud Mary, writer, Christian Swegal]
-
A.
Jan D'Alquen
Jan D'Alquen is a cinematographer best known for his work on the classic coming-of-age film "American Graffiti."
-
B.
Christian Huitema
Christian Huitema is a French computer scientist and Internet pioneer known for his influential work on networking protocols and IPv6 transition technologies.
-
C.
Simon Bisschop
Simon Bisschop, better known by the Latinized name Simon Episcopius, was a prominent 17th-century Dutch theologian and leading figure of the Remonstrant (Arminian) movement.
-
D.
Marius de Jonge
Marius de Jonge is a Dutch biblical scholar known for his influential work on New Testament studies and early Christianity.
-
E.
Roger Degueldre
Roger Degueldre was a French Army officer best known as a leading figure and commando leader in the pro–French Algeria paramilitary underground during the Algerian War.
- 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: Christian Swegal Triple: [Proud Mary, writer, Christian Swegal]
Generated description
Christian Swegal is a writer best known for his work on the film "Proud Mary."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christian Swegal Target entity description: Christian Swegal is a writer best known for his work on the film "Proud Mary."
-
A.
Jan D'Alquen
Jan D'Alquen is a cinematographer best known for his work on the classic coming-of-age film "American Graffiti."
-
B.
Christian Huitema
Christian Huitema is a French computer scientist and Internet pioneer known for his influential work on networking protocols and IPv6 transition technologies.
-
C.
Simon Bisschop
Simon Bisschop, better known by the Latinized name Simon Episcopius, was a prominent 17th-century Dutch theologian and leading figure of the Remonstrant (Arminian) movement.
-
D.
Marius de Jonge
Marius de Jonge is a Dutch biblical scholar known for his influential work on New Testament studies and early Christianity.
-
E.
Roger Degueldre
Roger Degueldre was a French Army officer best known as a leading figure and commando leader in the pro–French Algeria paramilitary underground during the Algerian War.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8757b648190a26181efbad09a43 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8a9c41908190b789765861bd9924 |
completed | May 8, 2026, 7:02 a.m. |
| NEDg | Description generation | batch_69fd8bd70488819083f40c38575f3071 |
completed | May 8, 2026, 7:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8d4f2e848190a3c4c423c0ffed50 |
completed | May 8, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:54 p.m.