Triple
T22918991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mondelez International |
E568804
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
LU
LU is a historic French biscuit brand known for iconic cookies such as Petit Beurre and Prince, now owned by Mondelēz International.
|
E1561833
|
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: LU | Statement: [Mondelez International, brand, LU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LU Context triple: [Mondelez International, brand, LU]
-
A.
LU
LU is the vehicle registration code for the German city of Ludwigshafen am Rhein in the state of Rhineland-Palatinate.
-
B.
LU
LU is the official vehicle registration code used on license plates for the Swiss canton of Lucerne.
-
C.
LU
LU is the standard abbreviation for the Liber Usualis, a widely used compendium of Gregorian chant for the Roman Catholic liturgy.
-
D.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
E.
LU
LU is the commonly used abbreviation for the University of Latvia, a major public research university in Riga.
- 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: LU Triple: [Mondelez International, brand, LU]
Generated description
LU is a historic French biscuit brand known for iconic cookies such as Petit Beurre and Prince, now owned by Mondelēz International.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LU Target entity description: LU is a historic French biscuit brand known for iconic cookies such as Petit Beurre and Prince, now owned by Mondelēz International.
-
A.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
B.
LU
LU is the standard abbreviation for the Liber Usualis, a widely used compendium of Gregorian chant for the Roman Catholic liturgy.
-
C.
LU
LU is the official vehicle registration code used on license plates for the Swiss canton of Lucerne.
-
D.
LU
LU is the IATA airport code assigned to LAN Express, a regional airline operating within the LATAM Airlines Group in Chile.
-
E.
LU
LU is the vehicle registration code for the German city of Ludwigshafen am Rhein in the state of Rhineland-Palatinate.
- F. None of above. chosen
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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d316188190901d9356c07110e3 |
completed | April 29, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bc242d8188190b8c4fba17337d787 |
completed | May 19, 2026, 1:52 a.m. |
| NEDg | Description generation | batch_6a0bc2ea198081909fac3f91b13e444d |
completed | May 19, 2026, 1:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bc36ee72c81908bb65de9d23a2c13 |
completed | May 19, 2026, 1:57 a.m. |
Created at: April 17, 2026, 3:42 p.m.