Triple
T8931764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Homeland |
E212671
|
entity |
| Predicate | hasEnglishTitle |
P3437
|
FINISHED |
| Object | My Homeland |
E212671
|
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: My Homeland | Statement: [My Homeland, hasEnglishTitle, My Homeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: My Homeland Context triple: [My Homeland, hasEnglishTitle, My Homeland]
-
A.
My Homeland
chosen
"My Homeland" is the English title of "Mawtini," a famous patriotic anthem widely regarded as a symbol of national pride in the Arab world.
-
B.
Our Fatherland
"Our Fatherland" is the English title of "Mer Hayrenik," the national anthem of Armenia.
-
C.
To My Country
"To My Country" is a patriotic poem by Indian writer Sarojini Naidu that expresses deep love and devotion to her homeland.
-
D.
I Love My Country
I Love My Country is a television game show format created by Talpa Media in which celebrity teams compete in quizzes and challenges about their home nation.
-
E.
My Country
"My Country" is the English title of "Negaraku," the national anthem of Malaysia.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668cdc0c8190b908fd23cbdef534 |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba63544081909394500f28b34ccb |
completed | April 3, 2026, 1:02 p.m. |
Created at: March 30, 2026, 6:57 p.m.