Triple
T6010438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V0 detector |
E133816
|
entity |
| Predicate | experiment |
P68730
|
FINISHED |
| Object | ALICE |
E3748
|
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: ALICE | Statement: [V0 detector, experiment, ALICE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ALICE Context triple: [V0 detector, experiment, ALICE]
-
A.
ALICE
chosen
ALICE is a major particle physics experiment at CERN’s Large Hadron Collider dedicated to studying heavy-ion collisions and the properties of quark–gluon plasma.
-
B.
ALICE
ALICE is a U.S. military load-bearing equipment system introduced in the 1970s to improve how soldiers carry gear in the field.
-
C.
Alice
Alice is one of the given names of Anne, Princess Royal, the only daughter of Queen Elizabeth II and Prince Philip.
-
D.
Alice
Alice is an American sitcom that aired from the mid-1970s to the mid-1980s, following a widowed waitress working at a roadside diner and the quirky people in her life.
-
E.
Alice
Alice is the curious young girl who serves as the main protagonist of Disney’s animated film "Alice in Wonderland."
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560bae148190ad4755defaaf471b |
completed | March 22, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c108a17bc88190b710a1858120a32d |
completed | March 23, 2026, 9:32 a.m. |
Created at: March 22, 2026, 4:06 p.m.