Triple
T8725703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monica Raymund |
E207125
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Raymund |
E752551
|
NE FINISHED |
How this triple was built (2 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: Raymund | Statement: [Monica Raymund, familyName, Raymund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raymund Context triple: [Monica Raymund, familyName, Raymund]
-
A.
Raymund
chosen
Raymund is a masculine given name, a spelling variant of Raymond commonly used in various European languages.
-
B.
Raymun
Raymun is a town located within Jordan's Jerash (Jarash) Governorate, known for its rural setting in the country's north.
-
C.
Ramon
Ramon is the surname of Ilan Ramon, the first Israeli astronaut and a payload specialist on the Space Shuttle Columbia.
-
D.
Julian de Guzman
Julian de Guzman is a retired Canadian midfielder who became one of the national team’s most influential players and the first Canadian to play in Spain’s La Liga.
-
E.
Michael De Guzman
Michael De Guzman is an American screenwriter best known for his work on the film "Jaws: The Revenge" and various television movies and series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d158b0481908249610458f97306 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf42b0f5808190863a1ca3c4e9c8d1 |
completed | April 3, 2026, 4:31 a.m. |
Created at: March 30, 2026, 6:36 p.m.