Triple
T4432668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan Lievens |
E95369
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jan |
E103749
|
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: Jan | Statement: [Jan Lievens, givenName, Jan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Context triple: [Jan Lievens, givenName, Jan]
-
A.
Jan
chosen
Jan is the Dutch given name of Jan Peter Balkenende, the former Prime Minister of the Netherlands.
-
B.
Jan
Jan is an alternative romanization of the name Zhan, used to represent the same underlying name in different transliteration systems.
-
C.
Jon
Jon is a masculine given name, often used as a shortened form or variant of names like Jonathan or John.
-
D.
Jones
Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
-
E.
Jonathan
Jonathan is a common masculine given name of Hebrew origin, meaning "Yahweh has given."
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3556cd83881908547aa311c4f17fa |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6137171148190b77a6f783d5cf315 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:31 p.m.