Triple
T1075040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Eberflus |
E23816
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Eberflus
Eberflus is the surname of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
|
E164644
|
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: Eberflus | Statement: [Matt Eberflus, familyName, Eberflus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eberflus Context triple: [Matt Eberflus, familyName, Eberflus]
-
A.
Inn River
The Inn River is a major Alpine river in Central Europe that flows through Switzerland, Austria, and Germany before joining the Danube.
-
B.
Leine
The Leine is a major river in central Germany that flows through the federal state of Lower Saxony, passing cities such as Göttingen and Hanover before joining the Aller.
-
C.
Saale
The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
-
D.
Lahn
The Lahn is a river in western Germany that flows through the states of North Rhine-Westphalia, Hesse, and Rhineland-Palatinate before joining the Rhine.
-
E.
Dommel
The Dommel is a river in the southern Netherlands and northern Belgium that flows through cities including Eindhoven before joining the Dieze.
- 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: Eberflus Triple: [Matt Eberflus, familyName, Eberflus]
Generated description
Eberflus is the surname of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eberflus Target entity description: Eberflus is the surname of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
-
A.
Inn River
The Inn River is a major Alpine river in Central Europe that flows through Switzerland, Austria, and Germany before joining the Danube.
-
B.
Leine
The Leine is a major river in central Germany that flows through the federal state of Lower Saxony, passing cities such as Göttingen and Hanover before joining the Aller.
-
C.
Saale
The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
-
D.
Lahn
The Lahn is a river in western Germany that flows through the states of North Rhine-Westphalia, Hesse, and Rhineland-Palatinate before joining the Rhine.
-
E.
Dommel
The Dommel is a river in the southern Netherlands and northern Belgium that flows through cities including Eindhoven before joining the Dieze.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92e480c81909a848b48c196a293 |
completed | March 1, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad089d492881909c6ef4519c087386 |
completed | March 8, 2026, 5:26 a.m. |
| NEDg | Description generation | batch_69ad0949cdf88190977da43dd53c72e0 |
completed | March 8, 2026, 5:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad09af636c81909d6bf5d65591624e |
completed | March 8, 2026, 5:31 a.m. |
Created at: March 1, 2026, 7:42 p.m.