Triple
T1747204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The King |
E38360
|
entity |
| Predicate | alias |
P39
|
FINISHED |
| Object |
Dauphin
The Dauphin was the traditional title given to the heir apparent to the throne of France under the Ancien Régime.
|
E195679
|
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: Dauphin | Statement: [The King, alias, Dauphin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dauphin Context triple: [The King, alias, Dauphin]
-
A.
Chouteau
Chouteau is a French-origin surname notably associated with a prominent fur-trading and founding family in early St. Louis and the American Midwest.
-
B.
Strathmore
Strathmore is a broad, fertile valley in eastern Scotland known for its rich agricultural land and historic settlements.
-
C.
Sainte-Marie
Sainte-Marie is a French designation for Saint Mary, the mother of Jesus, commonly used as a namesake for religious institutions and places.
-
D.
Saint‑Cloud
Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
-
E.
Concordia
Concordia is a significant city in the Mesopotamia region of northeastern Argentina, known for its agriculture, citrus production, and location along the Uruguay River.
- 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: Dauphin Triple: [The King, alias, Dauphin]
Generated description
The Dauphin was the traditional title given to the heir apparent to the throne of France under the Ancien Régime.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dauphin Target entity description: The Dauphin was the traditional title given to the heir apparent to the throne of France under the Ancien Régime.
-
A.
Chouteau
Chouteau is a French-origin surname notably associated with a prominent fur-trading and founding family in early St. Louis and the American Midwest.
-
B.
Strathmore
Strathmore is a broad, fertile valley in eastern Scotland known for its rich agricultural land and historic settlements.
-
C.
Sainte-Marie
Sainte-Marie is a French designation for Saint Mary, the mother of Jesus, commonly used as a namesake for religious institutions and places.
-
D.
Saint‑Cloud
Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
-
E.
Concordia
Concordia is a municipality in the Mexican state of Sinaloa, known for its colonial architecture and traditional crafts.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63eabdf48190878ecde3d1b1faf3 |
completed | March 6, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0e058948190939e936af8f0e221 |
completed | March 8, 2026, 4:16 p.m. |
| NEDg | Description generation | batch_69ada1a2122481909c7a3470e090af17 |
completed | March 8, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ada23515d08190833ad1a35bb7a265 |
completed | March 8, 2026, 4:22 p.m. |
Created at: March 4, 2026, 7:31 p.m.