Triple
T38060048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trafalgar Square Norwegian Christmas Tree |
E950315
|
entity |
| Predicate | firstGivenIn |
P207578
|
FINISHED |
| Object | 1947 |
—
|
LITERAL 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: 1947 | Statement: [Trafalgar Square Norwegian Christmas Tree, firstGivenIn, 1947]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstGivenIn Context triple: [Trafalgar Square Norwegian Christmas Tree, firstGivenIn, 1947]
-
A.
first
Indicates that one entity precedes all others in an ordered sequence or ranking.
-
B.
firstNamed
Indicates that the subject is the first entity to be given or assigned the specified name among a set or sequence of entities.
-
C.
firstOrdinary
Indicates that the subject is the first entity to hold or occupy an ordinary (non-special, standard) position, role, or status in a given sequence or context.
-
D.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
E.
firstWord
Indicates that one entity is the first word in the sequence or text associated with another entity.
- F. None of above. chosen
Provenance (4 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_69f76f01e63c819093b6012fc974f35a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037df009f4819082e04683e6e8a106 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:21 p.m.