Triple
T17026695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter the goatherd |
E413081
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object |
Peter
Peter is a traditional male given name of Greek origin, commonly used in many cultures and languages.
|
E30437
|
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: Peter | Statement: [Peter the goatherd, hasGivenName, Peter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Context triple: [Peter the goatherd, hasGivenName, Peter]
-
A.
Peter
Peter is one of the three allegorical brothers in Jonathan Swift’s satirical work "A Tale of a Tub," representing the excesses and corruptions of the Roman Catholic Church.
-
B.
Peter
Peter is the young prince falsely accused of murder and imprisoned in Stephen King’s fantasy novel "The Eyes of the Dragon," whose struggle to reclaim his throne drives the story.
-
C.
Peter
Peter is the young, adventurous orphan who becomes the boy that never grows up in the Peter and the Starcatcher prequel to the Peter Pan story.
-
D.
Peter
Peter is a recurring comedic character from the British sketch show "A Bit of Fry & Laurie."
-
E.
Peter
Peter is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s newsroom staff.
- 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: Peter Triple: [Peter the goatherd, hasGivenName, Peter]
Generated description
Peter is a traditional male given name of Greek origin, commonly used in many cultures and languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Target entity description: Peter is a traditional male given name of Greek origin, commonly used in many cultures and languages.
-
A.
Peter
chosen
Peter is a common male given name of Greek origin, widely used in many languages and cultures, often associated with the meaning "rock" or "stone."
-
B.
Peter
Peter is the middle name of John Peter Altgeld, a prominent 19th-century American politician and reformist governor of Illinois.
-
C.
Peter
Peter is a central figure among Jesus’s apostles in the New Testament, traditionally regarded as the leader of the early Christian Church.
-
D.
Peter
Peter is a leading apostle of Jesus in the New Testament, known for his prominent role in the early Christian church and for preaching key messages about Jesus’ resurrection.
-
E.
Peter
Peter is the brave young protagonist of Sergei Prokofiev’s symphonic fairy tale "Peter and the Wolf," known for capturing a wolf with the help of his animal friends.
- F. None of above.
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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d5ed388190871aa738cac04b65 |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b53306081908972a0a5db474b6c |
completed | May 10, 2026, 11:57 p.m. |
| NEDg | Description generation | batch_6a011cfb74b88190bbd5af862727790f |
completed | May 11, 2026, 12:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a011dad838c8190a1ea560680c9ca57 |
completed | May 11, 2026, 12:07 a.m. |
Created at: April 10, 2026, 5:33 a.m.