Triple
T22768382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris |
E563186
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object |
Matthew
Matthew is a male given name of Hebrew origin, commonly used in English-speaking countries and borne by numerous notable historical and contemporary figures.
|
E556162
|
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: Matthew | Statement: [Iris, associatedWithCharacter, Matthew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Context triple: [Iris, associatedWithCharacter, Matthew]
-
A.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
B.
John
John is the given name of John Randolph Hearst, a member of the prominent Hearst family associated with American media and publishing.
-
C.
John
John is the given name of Sir John Brown of Fordell, a Scottish nobleman and landowner.
-
D.
John
John A. Knebel is an American attorney and former government official who served as the United States Secretary of Agriculture under President Gerald Ford.
-
E.
John
John I of Navarre was a late 13th-century king who briefly ruled the Kingdom of Navarre and held the title of King of France as the posthumous son of Louis X.
- 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: Matthew Triple: [Iris, associatedWithCharacter, Matthew]
Generated description
Matthew is a male given name of Hebrew origin, commonly used in English-speaking countries and borne by numerous notable historical and contemporary figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Target entity description: Matthew is a male given name of Hebrew origin, commonly used in English-speaking countries and borne by numerous notable historical and contemporary figures.
-
A.
Matthew
chosen
Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
-
B.
Matthew
Matthew is the given name of Matt Le Tissier, the renowned former Southampton and England footballer known for his exceptional skill and loyalty to a single club.
-
C.
Matthew
Matthew is the given name of Sir Matt Busby, the legendary Scottish football manager best known for his long and successful tenure at Manchester United.
-
D.
Matthew
Matthew is the given first name of American actor Ryan Phillippe, known for films like "Cruel Intentions" and "Crash."
-
E.
Matthew
Matthew is the given name of the pioneering British Egyptologist and archaeologist Flinders Petrie, renowned for developing systematic excavation and seriation methods.
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b59c9cc8190a6edd68f3209a672 |
completed | April 29, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b981f3a1c819083a7d498290af751 |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b98d159688190a5ec037ee8692f33 |
completed | May 18, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b99b6e7e88190995319351374f97c |
completed | May 18, 2026, 10:59 p.m. |
Created at: April 17, 2026, 3:27 p.m.